Relevant bibliographies by topics / Filter Algorithmus

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Academic literature on the topic 'Filter Algorithmus'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Filter Algorithmus"

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Trendelenburg, S., J. Becker, F. Henrici, and Y. Manoli. "Synthese von analogen Filtern auf einer rekonfigurierbaren Hardware-Architektur mittels eines Genetischen Algorithmus." Advances in Radio Science 6 (May 26, 2008): 195–99. http://dx.doi.org/10.5194/ars-6-195-2008.

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Abstract. Rekonfigurierbare Analog-Arrays (FPAAs) sind der Versuch, die Vorteile der aus der digitalen Welt bekannten FPGAs (Flexibilität, Entwurfsgeschwindigkeit) auch für analoge Anwendungen verfügbar zu machen. Aufgrund der Vielfalt der analogen Schaltungstechnik ist die Abbildung von vorgegebenen Schaltungskonzepten auf eine FPAA-Architektur nicht immer einfach lösbar. Diese Arbeit stellt einen neuen Ansatz für die Synthese von Filtern auf einer FPAA-Architektur für zeitkontinuierliche Analogfilter mittels eines Genetischen Algorithmus (GA) vor. Anhand eines Matlab-Modells des FPAA, das eine gute übereinstimmung mit Simulationen des FPAA auf Transistorebene aufweist, wurde gezeigt, dass eine große Vielzahl verschiedener Filterstrukturen auf dieser Architektur dargestellt werden kann. Daraufhin wurde ein Genetischer Algorithmus entwickelt, der es erlaubt, aus einer gegebenen Filterspezifikation Konfigurationsdatensätze zu synthetisieren, die den gewünschten Filter auf die FPAA-Architektur abbilden.
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Buhmann, A., M. Keller, M. Maurer, M. Ortmanns, and Y. Manoli. "Ein Unscented Kalman Filter zur Schätzung von Schaltungsnichtidealitäten eines zeitkontinuierlichen Sigma-Delta Wandlers mit impliziter Dezimation." Advances in Radio Science 6 (May 26, 2008): 175–79. http://dx.doi.org/10.5194/ars-6-175-2008.

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Abstract. Nichtidealitäten einer Schaltung, wie z.B. nicht ideale Charakteristik des Operationsverstärkers und Streuungen in den Filterkoeffizienten, sind dahingehend bekannt die Effizienz von zeitkontinuierlichen Sigma-Delta Wandlern in drastischer Weise zu reduzieren. Daher stellt diese Veröffentlichung eine mögliche Methode vor, um die genannten Nichtidealitäten durch eine Schätzung mit Hilfe eines Unscented Kalman Filters zu bestimmen und in einem möglichen weiteren Schritt zu korrigieren. Des Weiteren kann durch eine leichte Modifikation des vorgestellten Algorithmus auch gleichzeitig eine implizite Dezimation des Ausgangssignals durchgeführt werden. Hierdurch wird die Gesamteffizienz des vorgestellten Ansatzes gesteigert, da kein zusätzlicher Dezimationsfilter mehr benötigt wird. Simulationsergebnisse des Filteralgorithmus zeigen die prinzipielle Funktion des Algorithmus.
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Battiston, Adrian, Inna Sharf, and Meyer Nahon. "Attitude estimation for collision recovery of a quadcopter unmanned aerial vehicle." International Journal of Robotics Research 38, no. 10-11 (August 8, 2019): 1286–306. http://dx.doi.org/10.1177/0278364919867397.

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An extensive evaluation of attitude estimation algorithms in simulation and experiments is performed to determine their suitability for a collision recovery pipeline of a quadcopter unmanned aerial vehicle. A multiplicative extended Kalman filter (MEKF), unscented Kalman filter (UKF), complementary filter, [Formula: see text] filter, and novel adaptive varieties of the selected filters are compared. The experimental quadcopter uses a PixHawk flight controller, and the algorithms are implemented using data from only the PixHawk inertial measurement unit (IMU). Performance of the aforementioned filters is first evaluated in a simulation environment using modified sensor models to capture the effects of collision on inertial measurements. Simulation results help define the efficacy and use cases of the conventional and novel algorithms in a quadcopter collision scenario. An analogous evaluation is then conducted by post-processing logged sensor data from collision flight tests, to gain new insights into algorithms’ performance in the transition from simulated to real data. The post-processing evaluation compares each algorithm’s attitude estimate, including the stock attitude estimator of the PixHawk controller, to data collected by an offboard infrared motion capture system. Based on this evaluation, two promising algorithms, the MEKF and an adaptive [Formula: see text] filter, are selected for implementation on the physical quadcopter in the control loop of the collision recovery pipeline. Experimental results show an improvement in the metric used to evaluate experimental performance, the time taken to recover from the collision, when compared with the stock attitude estimator on the PixHawk (PX4) software.
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Porsani, Milton J. "Fast algorithms to design discrete Wiener filters in lag and length coordinates." GEOPHYSICS 61, no. 3 (May 1996): 882–90. http://dx.doi.org/10.1190/1.1444013.

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Two recursive algorithms for designing discrete Wiener filters for wavelets of different phase characteristics are the Simpson and the Manolakis recursions. Both procedures are efficient; however, both recursions work with a prefixed length filter. Two fast algorithms to design discrete Wiener filters in lag and length coordinates are presented. The recursion methods of Levinson and Manolakis are combined to generate two fast algorithms that calculate the value for the minimized total squared error (MTSE) corresponding to spiking and shaping filters. For a spiking filter of length n and a wavelet of m data points, [Formula: see text] operations are required to obtain the [Formula: see text] map of the MTSEs, (one operation is defined here as one multiplication and one addition). For a shaping filter, [Formula: see text] operations are required to obtain the corresponding m × n map. These algorithms may be seen as a Levinson recursion on two variables, length j of the filter and lag k, for the desired signal. Numerical examples for spiking and shaping filters are presented.
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Befigiannis, G. N., E. N. Demiris, and S. D. Likothanassis. "Evolutionary Nonlinear Multimodel Partitioning Filters." Journal of Advanced Computational Intelligence and Intelligent Informatics 5, no. 1 (January 20, 2001): 8–14. http://dx.doi.org/10.20965/jaciii.2001.p0008.

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The problem of designing adaptive filters for nonlinear systems is faced in this work. The proposed evolution program combines the effectiveness of multimodel adaptive filters and the robustness of genetic algorithms (GAs). Specifically, a bank of different extended Kalman filters is implemented. Then, the a posteriori probability that a specific model of the bank of conditional models is the true one can be used as a GA fitness function. The superiority of the algorithm is that it evolves concurrently the models’ population with initial conditions. Thus, this procedure alleviates extended Kalman filter sensitivity in initial conditions, by estimating the best values. In addition to this, adaptive implementation is proposed that relieves the disadvantage of time-consuming GA implementation. Finally, a variety of defined crossover and mutation operators is investigated in order to accelerate the algorithm’s convergence.
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Wang, Guoqing, Ning Li, and Yonggang Zhang. "Hybrid consensus sigma point approximation nonlinear filter using statistical linearization." Transactions of the Institute of Measurement and Control 40, no. 8 (May 2018): 2517–25. http://dx.doi.org/10.1177/0142331217691758.

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In this paper, a hybrid consensus sigma point approximation nonlinear filter is proposed for state estimation in collaborative sensor network, where hybrid consensus of both measurement and information is utilised. Statistical linearization of nonlinear functions is used in sigma point filters, that is, unscented Kalman filter (UKF), cubature Kalman filter (CKF), and central difference Kalman filter (CDKF). Stability of the proposed algorithm is also analysed with the help of linearization operation and some conservative assumptions. Two typical target tracking examples are used to demonstrate the effectiveness of the proposed algorithms. Simulation results show that the proposed algorithms are more stable than existing algorithms, and among our proposed algorithms, CKF- and CDKF-based algorithms are more accurate and stable than the UKF-based one.
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Saha, Suman Kumar, R. Kar, D. Mandal, and S. P. Ghoshal. "A Novel Firefly Algorithm for Optimal Linear Phase FIR Filter Design." International Journal of Swarm Intelligence Research 4, no. 2 (April 2013): 29–48. http://dx.doi.org/10.4018/jsir.2013040102.

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Optimal digital filter design in digital signal processing has thrown a growing influence on communication systems. FIR filter design involves multi-parameter optimization, on which the existing optimization algorithms do not work efficiently. For which different optimization techniques can be utilized to determine the impulse response coefficient of a filter and try to meet the ideal frequency response characteristics. In this paper, FIR low pass, high pass, band pass and band stop filters have been designed using a new meta-heuristic search method, called firefly algorithm. Firefly Algorithm is inspired by the flash pattern and characteristics of fireflies. The performance of the designed filters has been compared with that obtained by real coded genetic algorithm (RGA), standard PSO and differential evolution (DE) optimization techniques. Differential evolution (DE) is already one of the most powerful stochastic real-parameter optimization algorithms in current use. Here the firefly algorithm (FA) technique has proven a significant advantage. For the problem at hand, the simulation of designing FIR filters has been done and the simulation results demonstrate that Firefly algorithm is better than other relevant algorithms, not only in the convergence speed but also in the performance of the designed filter.
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Hu, J., R. Guo, X. Zhu, G. Baier, and Y. Wang. "NON-LOCAL MEANS FILTER FOR POLARIMETRIC SAR SPECKLE REDUCTION-EXPERIMENTS USING TERRASAR-X DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W4 (March 11, 2015): 71–77. http://dx.doi.org/10.5194/isprsannals-ii-3-w4-71-2015.

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The speckle is omnipresent in synthetic aperture radar (SAR) images as an intrinsic characteristic. However, it is unwanted in certain applications. Therefore, intelligent filters for speckle reduction are of great importance. It has been demonstrated in several literatures that the non-local means filter can reduce noise while preserving details. This paper discusses non-local means filter for polarimetric SAR (PolSAR) speckle reduction. The impact of different similarity approaches, weight kernels, and parameters in the filter were analysed. A data-driven adaptive weight kernel was proposed. Combined with different similarity measures, it is compared with existing algorithms, using fully polarimetric TerraSAR-X data acquired during the commissioning phase. The proposed approach has overall the best performance in terms of speckle reduction, detail preservation, and polarimetric information preservation. This study suggests the high potential of using the developed non- local means filer for speckle reduction of PolSAR data acquired by the next generation SAR missions, e.g. TanDEM-L and TerraSAR-X NG.
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Lele, Celestin. "Folding Theory for Fantastic Filters in BL-Algebras." International Journal of Artificial Life Research 2, no. 4 (October 2011): 32–42. http://dx.doi.org/10.4018/ijalr.2011100104.

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In this paper, the author examines the notion of n-fold fantastic and fuzzy n-fold fantastic filters in BL-algebras. Several characterizations of fuzzy n-fold fantastic filters are given. The author shows that every n-fold (fuzzy n-fold) fantastic filter is a filter (fuzzy filter), but the converse is not true. Using a level set of a fuzzy set in a BL-algebra, the author gives a characterization of fuzzy n-fold fantastic filters. Finally, the author establishes the extension property for n-fold and fuzzy n-fold fantastic filters in BL-algebras. The author also constructs some algorithms for folding theory applied to fantastic filters in BL-algebras.
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Wang, Lijun, Sisi Wang, and Wenzhi Yang. "Adaptive federated filter for multi-sensor nonlinear system with cross-correlated noises." PLOS ONE 16, no. 2 (February 19, 2021): e0246680. http://dx.doi.org/10.1371/journal.pone.0246680.

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This paper presents an adaptive approach to the federated filter for multi-sensor nonlinear systems with cross-correlations between process noise and local measurement noise. The adaptive Gaussian filter is used as the local filter of the federated filter for the first time, which overcomes the performance degradation caused by the cross-correlated noises. Two kinds of adaptive federated filters are proposed, one uses a de-correlation framework as local filter, and the subfilter of the other one is defined as a Gaussian filter with correlated noises at the same-epoch, and much effort is made to verify the theoretical equivalence of the two algorithms in the nonlinear fusion system. Simulation results show that the proposed algorithms are superior to the traditional federated filter and Gaussian filter with same-paced correlated noises, and the equivalence between the proposed algorithms and high degree cubature federated filter is also demonstrated.
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Dissertations / Theses on the topic "Filter Algorithmus"

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Law, Ying Man. "Iterative algorithms for the constrained design of filters and filter banks /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202004%20LAW.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004.
Includes bibliographical references (leaves 108-111). Also available in electronic version. Access restricted to campus users.
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Baicher, Gurvinder Singh. "Towards optimisation of digital filters and multirate filter banks through genetic algorithms." Thesis, University of South Wales, 2003. https://pure.southwales.ac.uk/en/studentthesis/towards-optimisation-of-digital-filters-and-multirate-filter-banks-through-genetic-algorithms(1ed2778b-e27b-4434-bc50-915f697a0d6b).html.

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This thesis is concerned with the issues of design and optimisation of digital filters and multirate filter banks. The main focus and contribution of this thesis is to apply the genetic algorithm (GA) technique and to draw some comparison with the standard gradient and non-gradient based optimisation methods. The finite word length (FWL) constraint affects the accuracy of a real-time digital filter requency response. For the case of digital filters, this study is concerned with the optimisation of FWL coefficients using genetic algorithms. Some comparative study with the simple hill climber algorithms is also included. The outcome of this part of the study demonstrates a substantial improvement of the new results when compared with the simply rounded FWL coefficient frequency response. The FWL coefficient optimisation process developed in the earlier Chapters is extended to the field of multirate filter banks. All multirate filter banks suffer from the problems of amplitude, phase and aliasing errors and, therefore, constraints for perfect reconstruction (PR) of the input signal can be extensive. The problem, in general, is reduced to relaxing constraints at the expense of errors and finding methods for minimising the errors. Optimisation techniques are thus commonly used for the design and implementation of multirate filter banks. In this part of the study, GAs have been used in two distinct stages. Firstly, for the design optimisation so that the overall errors are minimised and secondly for FWL coefficient optimisation of digital filters that form the sub-band filters of the filter bank. This process leads to an optimal realisation of the filter bank that can be applied to specific applications such as telephony speech signal coding and compression. One example of the optimised QMF bank was tested on a real-time DSP target system and the results are reported. The multiple M-channel uniform and non-uniform filter banks have also been considered in this study for design optimisation. For a comparative study of the GA optimised results of the design stage of the filter bank, other standard methods such as the gradient based quasi-Newton and the non-gradient based downhill Simplex methods were also used. In general, the outcome of this part of study demonstrates that a hybrid approach of GA and standard method was the most efficient and effective process in generating the best results.
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Sridharan, M. K. "Subband Adaptive Filtering Algorithms And Applications." Thesis, Indian Institute of Science, 2000. http://hdl.handle.net/2005/266.

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In system identification scenario, the linear approximation of the system modelled by its impulse response, is estimated in real time by gradient type Least Mean Square (LMS) or Recursive Least Squares (RLS) algorithms. In recent applications like acoustic echo cancellation, the order of the impulse response to be estimated is very high, and these traditional approaches are inefficient and real time implementation becomes difficult. Alternatively, the system is modelled by a set of shorter adaptive filters operating in parallel on subsampled signals. This approach, referred to as subband adaptive filtering, is expected to reduce not only the computational complexity but also to improve the convergence rate of the adaptive algorithm. But in practice, different subband adaptive algorithms have to be used to enhance the performance with respect to complexity, convergence rate and processing delay. A single subband adaptive filtering algorithm which outperforms the full band scheme in all applications is yet to be realized. This thesis is intended to study the subband adaptive filtering techniques and explore the possibilities of better algorithms for performance improvement. Three different subband adaptive algorithms have been proposed and their performance have been verified through simulations. These algorithms have been applied to acoustic echo cancellation and EEG artefact minimization problems. Details of the work To start with, the fast FIR filtering scheme introduced by Mou and Duhamel has been generalized. The Perfect Reconstruction Filter Bank (PRFB) is used to model the linear FIR system. The structure offers efficient implementation with reduced arithmetic complexity. By using a PRFB with non adjacent filters non overlapping, many channel filters can be eliminated from the structure. This helps in reducing the complexity of the structure further, but introduces approximation in the model. The modelling error depends on the stop band attenuation of the filters of the PRFB. The error introduced due to approximation is tolerable for applications like acoustic echo cancellation. The filtered output of the modified generalized fast filtering structure is given by (formula) where, Pk(z) is the main channel output, Pk,, k+1 (z) is the output of auxiliary channel filters at the reduced rate, Gk (z) is the kth synthesis filter and M the number of channels in the PRFB. An adaptation scheme is developed for adapting the main channel filters. Auxiliary channel filters are derived from main channel filters. Secondly, the aliasing problem of the classical structure is reduced without using the cross filters. Aliasing components in the estimated signal results in very poor steady state performance in the classical structure. Attempts to eliminate the aliasing have reduced the computation gain margin and the convergence rate. Any attempt to estimate the subband reference signals from the aliased subband input signals results in aliasing. The analysis filter Hk(z) having the following antialiasing property (formula) can avoid aliasing in the input subband signal. The asymmetry of the frequency response prevents the use of real analysis filters. In the investigation presented in this thesis, complex analysis filters and real'synthesis filters are used in the classical structure, to reduce the aliasing errors and to achieve superior convergence rate. PRFB is traditionally used in implementing Interpolated FIR (IFIR) structure. These filters may not be ideal for processing an input signal for an adaptive algorithm. As third contribution, the IFIR structure is modified using discrete finite frames. The model of an FIR filter s is given by Fc, with c = Hs. The columns of the matrix F forms a frame with rows of H as its dual frame. The matrix elements can be arbitrary except that the transformation should be implementable as a filter bank. This freedom is used to optimize the filter bank, with the knowledge of the input statistics, for initial convergence rate enhancement . Next, the proposed subband adaptive algorithms are applied to acoustic echo cancellation problem with realistic parameters. Speech input and sufficiently long Room Impulse Response (RIR) are used in the simulations. The Echo Return Loss Enhancement (ERLE)and the steady state error spectrum are used as performance measures to compare these algorithms with the full band scheme and other representative subband implementations. Finally, Subband adaptive algorithm is used in minimization of EOG (Electrooculogram) artefacts from measured EEG (Electroencephalogram) signal. An IIR filterbank providing sufficient isolation between the frequency bands is used in the modified IFIR structure and this structure has been employed in the artefact minimization scheme. The estimation error in the high frequency range has been reduced and the output signal to noise ratio has been increased by a couple of dB over that of the fullband scheme. Conclusions Efforts to find elegant Subband adaptive filtering algorithms will continue in the future. However, in this thesis, the generalized filtering algorithm could offer gain in filtering complexity of the order of M/2 and reduced misadjustment . The complex classical scheme offered improved convergence rate, reduced misadjustment and computational gains of the order of M/4 . The modifications of the IFIR structure using discrete finite frames made it possible to eliminate the processing delay and enhance the convergence rate. Typical performance of the complex classical case for speech input in a realistic scenario (8 channel case), offers ERLE of more than 45dB. The subband approach to EOG artefact minimization in EEG signal was found to be superior to their fullband counterpart. (Refer PDF file for Formulas)
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Langer, Max. "Design of Fast Multidimensional Filters by Genetic Algorithms." Thesis, Linköping University, Department of Biomedical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2704.

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The need for fast multidimensional signal processing arises in many areas. One of the more demanding applications is real time visualization of medical data acquired with e.g. magnetic resonance imaging where large amounts of data can be generated. This data has to be reduced to relevant clinical information, either by image reconstruction and enhancement or automatic feature extraction. Design of fast-acting multidimensional filters has been subject to research during the last three decades. Usually methods for fast filtering are based on applying a sequence of filters of lower dimensionality acquired by e.g. weighted low-rank approximation. Filter networks is a method to design fast multidimensional filters by decomposing multiple filters into simpler filter components in which coefficients are allowed to be sparsely scattered. Up until now, coefficient placement has been done by hand, a procedure which is time-consuming and difficult. The aim of this thesis is to investigate whether genetic algorithms can be used to place coefficients in filter networks. A method is developed and tested on 2-D filters and the resulting filters have lower distortion values while still maintaining the same or lower number of coefficients than filters designed with previously known methods.

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Penberthy, Harris Stephen. "Natural algorithms in digital filter design." Thesis, University of Plymouth, 2001. http://hdl.handle.net/10026.1/2752.

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Digital filters are an important part of Digital Signal Processing (DSP), which plays vital roles within the modern world, but their design is a complex task requiring a great deal of specialised knowledge. An analysis of this design process is presented, which identifies opportunities for the application of optimisation. The Genetic Algorithm (GA) and Simulated Annealing are problem-independent and increasingly popular optimisation techniques. They do not require detailed prior knowledge of the nature of a problem, and are unaffected by a discontinuous search space, unlike traditional methods such as calculus and hill-climbing. Potential applications of these techniques to the filter design process are discussed, and presented with practical results. Investigations into the design of Frequency Sampling (FS) Finite Impulse Response (FIR) filters using a hybrid GA/hill-climber proved especially successful, improving on published results. An analysis of the search space for FS filters provided useful information on the performance of the optimisation technique. The ability of the GA to trade off a filter's performance with respect to several design criteria simultaneously, without intervention by the designer, is also investigated. Methods of simplifying the design process by using this technique are presented, together with an analysis of the difficulty of the non-linear FIR filter design problem from a GA perspective. This gave an insight into the fundamental nature of the optimisation problem, and also suggested future improvements. The results gained from these investigations allowed the framework for a potential 'intelligent' filter design system to be proposed, in which embedded expert knowledge, Artificial Intelligence techniques and traditional design methods work together. This could deliver a single tool capable of designing a wide range of filters with minimal human intervention, and of proposing solutions to incomplete problems. It could also provide the basis for the development of tools for other areas of DSP system design.
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Gurrapu, Omprakash. "Adaptive filter algorithms for channel equalization." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-19219.

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Equalization techniques compensate for the time dispersion introduced bycommunication channels and combat the resulting inter-symbol interference (ISI) effect.Given a channel of unknown impulse response, the purpose of an adaptive equalizer is tooperate on the channel output such that the cascade connection of the channel and theequalizer provides an approximation to an ideal transmission medium. Typically,adaptive equalizers used in digital communications require an initial training period,during which a known data sequence is transmitted. A replica of this sequence is madeavailable at the receiver in proper synchronism with the transmitter, thereby making itpossible for adjustments to be made to the equalizer coefficients in accordance with theadaptive filtering algorithm employed in the equalizer design. This type of equalization isknown as Non-Blind equalization. However, in practical situations, it would be highlydesirable to achieve complete adaptation without access to a desired response. Clearly,some form of Blind equalization has to be built into the receiver design. Blind equalizerssimultaneously estimate the transmitted signal and the channel parameters, which mayeven be time-varying. The aim of the project is to study the performance of variousadaptive filter algorithms for blind channel equalization through computer simulations.
Uppsatsnivå: D
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Huang, Yuchen. "Adaptive Notch Filter." PDXScholar, 1994. https://pdxscholar.library.pdx.edu/open_access_etds/4802.

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The thesis presents a new adaptive notch filter (ANF) algorithm that is more accurate and efficient and has a faster convergent rate than previous ANF algorithms. In 1985, Nehorai designed an infinite impulse response (UR) ANF algorithm that has many advantages over previous ANF algorithms. It requires a minimal number of parameters with constrained poles and zeros. It has higher stability and sharper notches than any ANF algorithm until now. Because of the special filter structure and the recursive prediction error (RPE) method, however, the algorithm is very sensitive to the initial estimate of the filter coefficient and its covariance. Furthermore, convergence to the true filter coefficient is not guaranteed since the error-performance surface of the filter has its global minimum lying on a fairly flat region. We propose a new ANF algorithm that overcomes the convergence problem. By choosing a smaller notch bandwidth control parameter that makes the error-performance surface less flat, we can more easily detect a global minimum. We also propose a new convergence criterion to be used with the algorithm and a self-adjustment feature to reset the initial estimate of the filter coefficient and its covariance. This results in guaranteed convergence with more accurate results and more efficient computations than previous ANF algorithms.
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Clark, Matthew David. "Electronic Dispersion Compensation For Interleaved A/D Converters in a Standard Cell ASIC Process." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16269.

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The IEEE 802.3aq standard recommends a multi-tap decision feedback equalizer be implemented to remove inter-symbol interference and additive system noise from data transmitted over a 10 Gigabit per Second (10 Gbps) multi-mode fiber-optic link (MMF). The recommended implementation produces a design in an analog process. This design process is difficult, time consuming, and is expensive to modify if first pass silicon success is not achieved. Performing the majority of the design in a well-characterized digital process with stable, evolutionary tools reduces the technical risk. ASIC design rule checking is more predictable than custom tools flows and produces regular, repeatable results. Register Transfer Language (RTL) changes can also be relatively quickly implemented when compared to the custom flow. However, standard cell methodologies are expected to achieve clock rates of roughly one-tenth of the corresponding analog process. The architecture and design for a parallel linear equalizer and decision feedback equalizer are presented. The presented design demonstrates an RTL implementation of 10 GHz filters operating in parallel at 625 MHz. The performance of the filters is characterized by testing the design against a set of 324 reference channels. The results are compared against the IEEE standard group s recommended implementation. The linear equalizer design of 20 taps equalizes 88 % of the reference channels. The decision feedback equalizer design of 20 forward and 1 reverse tap equalizes 93 % of the reference channels. Analysis of the unequalized channels in performed, and areas for continuing research are presented.
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Tseng, Chien H. "Iterative algorithms for envelope-constrained filter design." Curtin University of Technology, Australian Telecommunications Research Institute, 1999. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=10453.

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The design of envelope-constrained (EC) filters is considered for the time-domain synthesis of filters for signal processing problems. The objective is to achieve minimal noise enhancement where the shape of the filter output to a specified input signal is constrained to lie within prescribed upper and lower bounds. Traditionally, problems of this type were treated by using the least-square (LS) approach. However, in many practical signal processing problems, this "soft" least-square approach is unsatisfactory because large narrow excursions from the desired shape occur so that the norm of the filter can be large and the choice of an appropriate weighting function is not obvious. Moreover, the solution can be sensitive to the detailed structure of the desired pulse, and it is usually not obvious how the shape of the desired pulse should be altered in order to improve on the solution. The "hard" EC filter formulation is more relevant than the "soft" LS approach in a variety of signal processing fields such as robust antenna and filter design, communication channel equalization, and pulse compression in radar and sonar. The distinctive feature is the set of inequality constraints on the output waveform: rather than attempting to match a specific desired pulse, we deal with a whole set of allowable outputs and seek an optimal point of that set.The EC optimal filter design problems involve a convex quadratic cost function and a number of linear inequality constraints. These EC filtering problems are classified into: discrete-time EC filtering problem, continuous-time EC filtering problem, and adaptive discrete-time EC filtering problem.The discrete-time EC filtering problem is handled using the discrete Lagrangian duality theory in combination with the space transformation function. The optimal solution of the dual problem can be computed by finding the limiting point of ++
an ordinary differential equation given in terms of the gradient flow. Two iterative algorithms utilizing the simple structure of the gradient flow are developed via discretizing the differential equations. Their convergence properties are derived for a deterministic environment. From the primal-dual relationship, the corresponding sequence of approximate solutions to the original discrete-time EC filtering problem is obtained.The continuous-time EC filtering problem (semi-infinite convex programming problem) is handled using the continuous Lagrangian duality theory and Caratheodory's dimensionality theory. Several important properties are derived and discussed in relation to practical engineering requirements. These include the observation that the continuous-time optimal filter via orthonormal filters has the structure of a matched filter in cascade with another filter. Furthermore, the semi-infinite convex programming problem is converted into an equivalent finite dual optimization problem, which can be solved by the optimization methods developed. Another issue, which relates to the continuous-time optimal filter design problem, is the design of robust optimal EC filters. The robustness issue arises because the solution of the EC filtering problem lies on the boundary of the feasible region. Thus, any disturbance in the prescribed input signal or errors in the implementation of the optimal filter are likely to result in the output constraints being violated. A detailed formulation and a corresponding design method for improving the robustness of optimal EC filters are given.Finally, an adaptive algorithm suitable for a stochastic environment is presented. The convergence properties of the algorithm in a stochastic environment are established.
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Carcanague, Sébastien. "Low-cost GPS/GLONASS Precise Positioning algorithm in Constrained Environment." Thesis, Toulouse, INPT, 2013. http://www.theses.fr/2013INPT0004/document.

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Le GNSS (Global Navigation Satellite System), et en particulier sa composante actuelle le système américain GPS et le système russe GLONASS, sont aujourd'hui utilisés pour des applications géodésiques afin d'obtenir un positionnement précis, de l'ordre du centimètre. Cela nécessite un certain nombre de traitements complexes, des équipements coûteux et éventuellement des compléments au sol des systèmes GPS et GLONASS. Ces applications sont aujourd'hui principalement réalisées en environnement « ouvert » et ne peuvent fonctionner en environnement plus contraint. L'augmentation croissante de l'utilisation du GNSS dans des domaines variés va voir émerger de nombreuses applications où le positionnement précis sera requis (par exemple des applications de transport/guidage automatique ou d'aide à la conduite nécessitant des performances importantes en terme de précision mais aussi en terme de confiance dans la position –l'intégrité- et de robustesse et disponibilité). D'autre part, l'arrivée sur le marché de récepteurs bas-coûts (inférieur à 100 euros) capables de poursuivre les signaux provenant de plusieurs constellations et d'en délivrer les mesures brutes laisse entrevoir des avancées importantes en termes de performance et de démocratisation de ces techniques de positionnement précis. Dans le cadre d'un utilisateur routier, l'un des enjeux du positionnement précis pour les années à venir est ainsi d'assurer sa disponibilité en tout terrain, c'est-à-dire dans le plus grand nombre d'environnements possibles, dont les environnements dégradés (végétation dense, environnement urbain, etc.) Dans ce contexte, l'objectif de la thèse a été d'élaborer et d'optimiser des algorithmes de positionnement précis (typiquement basés sur la poursuite de la phase de porteuse des signaux GNSS) afin de prendre en compte les contraintes liées à l'utilisation d'un récepteur bas coût et à l'environnement. En particulier, un logiciel de positionnement précis (RTK) capable de résoudre les ambiguïtés des mesures de phase GPS et GLONASS a été développé. La structure particulière des signaux GLONASS (FDMA) requiert notamment un traitement spécifiques des mesures de phase décrit dans la thèse afin de pouvoir isoler les ambiguïtés de phase en tant qu'entiers. Ce traitement est compliqué par l'utilisation de mesures provenant d'un récepteur bas coût dont les canaux GLONASS ne sont pas calibrés. L'utilisation d'une méthode de calibration des mesures de code et de phase décrite dans la thèse permet de réduire les biais affectant les différentes mesures GLONASS. Il est ainsi démontré que la résolution entière des ambiguïtés de phase GLONASS est possible avec un récepteur bas coût après calibration de celui-ci. La faible qualité des mesures, du fait de l'utilisation d'un récepteur bas coût en milieu dégradé est prise en compte dans le logiciel de positionnement précis en adoptant une pondération des mesures spécifique et des paramètres de validation de l'ambiguïté dépendant de l'environnement. Enfin, une méthode de résolution des sauts de cycle innovante est présentée dans la thèse, afin d'améliorer la continuité de l'estimation des ambiguïtés de phase. Les résultats de 2 campagnes de mesures effectuées sur le périphérique Toulousain et dans le centre-ville de Toulouse ont montré une précision de 1.5m 68% du temps et de 3.5m 95% du temps dans un environnement de type urbain. En milieu semi-urbain type périphérique, cette précision atteint 10cm 68% du temps et 75cm 95% du temps. Finalement, cette thèse démontre la faisabilité d'un système de positionnement précis bas-coût pour un utilisateur routier
GNSS and particularly GPS and GLONASS systems are currently used in some geodetic applications to obtain a centimeter-level precise position. Such a level of accuracy is obtained by performing complex processing on expensive high-end receivers and antennas, and by using precise corrections. Moreover, these applications are typically performed in clear-sky environments and cannot be applied in constrained environments. The constant improvement in GNSS availability and accuracy should allow the development of various applications in which precise positioning is required, such as automatic people transportation or advanced driver assistance systems. Moreover, the recent release on the market of low-cost receivers capable of delivering raw data from multiple constellations gives a glimpse of the potential improvement and the collapse in prices of precise positioning techniques. However, one of the challenge of road user precise positioning techniques is their availability in all types of environments potentially encountered, notably constrained environments (dense tree canopy, urban environments…). This difficulty is amplified by the use of low-cost receivers and antennas, which potentially deliver lower quality measurements. In this context the goal of this PhD study was to develop a precise positioning algorithm based on code, Doppler and carrier phase measurements from a low-cost receiver, potentially in a constrained environment. In particular, a precise positioning software based on RTK algorithm is described in this PhD study. It is demonstrated that GPS and GLONASS measurements from a low-cost receivers can be used to estimate carrier phase ambiguities as integers. The lower quality of measurements is handled by appropriately weighting and masking measurements, as well as performing an efficient outlier exclusion technique. Finally, an innovative cycle slip resolution technique is proposed. Two measurements campaigns were performed to assess the performance of the proposed algorithm. A horizontal position error 95th percentile of less than 70 centimeters is reached in a beltway environment in both campaigns, whereas a 95th percentile of less than 3.5 meters is reached in urban environment. Therefore, this study demonstrates the possibility of precisely estimating the position of a road user using low-cost hardware
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Books on the topic "Filter Algorithmus"

1

Rorabaugh, C. Britton. Digital filter designer's handbook: With C++ algorithms. 2nd ed. New York: McGraw-Hill, 1997.

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Rich, Thomas H. Algorithms for computer aided design of digital filters. Monterey, Calif: Naval Postgraduate School, 1988.

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Gould, N. I. M. A multidimensional filter algorithm for nonlinear equation and nonlinear least squares. Chilton: Rutherford Appleton Laboratory, 2003.

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Carpenter, J. Russell. Progress in navigation filter estimate fusion and its application to spacecraft rendezvous. [Washington, D.C.]: National Aeronautics and Space Administration, 1994.

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Carpenter, J. Russell. Progress in navigation filter estimate fusion and its application to spacecraft rendezvous. [Washington, D.C.]: National Aeronautics and Space Administration, 1994.

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Solo, Victor. Adaptive signal processing algorithms: Stability and performance. Englewood Cliffs, N.J: Prentice Hall, 1995.

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Gould, N. I. M. Global convergence of a non-monotone trust-region filter algorithm for nonlinear programming. Chilton: Rutherford Appleton Laboratory, 2003.

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Nerger, Lars. Parallel filter algorithms for data assimilation in oceanography =: Parallele Filteralgorithmen zur Datenassimilation in der Ozeanographie. Bremerhaven: Alfred-Wegener-Institut für Polar- und Meeresforschung, 2004.

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Nicklas, Richard B. An application of a Kalman Filter Fixed Interval Smoothing Algorithm to underwater target tracking. Monterey, Calif: Naval Postgraduate School, 1989.

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Adaptive filtering: Algorithms and practical implementation. 2nd ed. Boston: Kluwer Academic Publishers, 2002.

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Book chapters on the topic "Filter Algorithmus"

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Wanhammar, Lars, and Tapio Saramäki. "Filter Algorithms." In Digital Filters Using MATLAB, 73–107. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-24063-9_3.

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Pitas, I., and A. N. Venetsanopoulos. "Algorithms and Architectures." In Nonlinear Digital Filters, 345–87. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-6017-0_11.

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Bölcskei, Helmut, and Franz Hlawatsch. "Oversampled modulated filter banks." In Gabor Analysis and Algorithms, 295–322. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-2016-9_10.

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Mulgrew, Bernard, and Colin F. N. Cowan. "Adaptive FIR Filter Algorithms." In The Kluwer International Series in Engineering and Computer Science, 15–57. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1701-2_2.

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Abdelgawad, Ahmed, and Magdy Bayoumi. "Kalman Filter." In Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks, 59–76. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1350-9_4.

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Naor, Moni, and Eylon Yogev. "Sliding Bloom Filters." In Algorithms and Computation, 513–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45030-3_48.

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Patidar, Pawan Kumar, and Mukesh Kataria. "Image Enhancement Performance of Fuzzy Filter and Wiener Filter for Statistical Distortion." In Algorithms for Intelligent Systems, 583–94. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4936-6_63.

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Rawlins, Michael W. "Calibration Filter." In Low Power Wireless Receivers for IoT Applications with Multi-band Calibration Algorithms, 19–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70729-3_3.

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Shukla, K. K., and Arvind K. Tiwari. "Filter Banks and DWT." In Efficient Algorithms for Discrete Wavelet Transform, 21–36. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4941-5_2.

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Gay, Steven L. "Affine Projection Algorithms." In Least-Mean-Square Adaptive Filters, 241–91. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471461288.ch7.

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Conference papers on the topic "Filter Algorithmus"

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Schoen, Marco P., Bhag Singh Kelwant Kaur, Sinchai Chinvorarat, and Chien-Hsun Kuo. "Predictive Intelligent Filter Design in Signal Processing Using AR and ARMA Models." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59585.

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The design of filters for the prediction of signals has been a widely studied field. For some of the applications, more accurate and further reaching algorithms are necessary. For example, in the prediction of irregular waves for wave energy converters, an accurate prediction of wave height and velocity are important in order to maximize the converter’s efficiency. This paper presents three prediction filters for such an application. The first algorithm is based on a simple autoregressive (AR) model and a standard least-squares estimation scheme. The second proposed filter is based on an autoregressive moving average (ARMA) model. The third filter is a fixed horizon predictive filter based on an AR structure, using a Genetic Algorithm to estimate its prediction parameters. All proposed algorithms are simulated using a Pierson-Moskowitz spectrum representing wind speeds of 30 knot.
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Schoen, Marco P. "Dynamic Compensation of Intelligent Sensors." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-42275.

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Commercial sensors have generally, due to their own characteristics, some undesirable influences on the measured quantity and its precision. In particular, the dynamic characteristics can be reflected on to the measured quantity and lead to false or delayed interpretation of the underlying physical process. The quality and therefore the cost of the sensor is often tied with the dynamic performance of these instruments. Intelligent sensors are able to adapt to changing environments, calibrate themselves, and predict the pattern of the future signal. This paper presents algorithms to improve the dynamic performance of sensors, identify the dynamic characteristics of the sensor, and to predict the future pattern of the measured quantity. In particular, two inverse filters are proposed for the improvement of the sensors dynamic performance. One filter incorporates an optimal constant feedback gain that reduces the computational cost and increases the accuracy. A system identification method is used to identify the sensor’s dynamic properties and allows for adaptation of the inverse filter’s parameters. This identification algorithm computes the optimum input to the system i.e. the sensor. The optimization is based on the inverse correlation matrix of the information matrix. A genetic algorithm is used to perform both optimizations, for the computation of the optimal input, and for the optimal constant feedback gain. In addition, a predictive filter formulation is given that is based on the identified system. Simulation results indicate that both inverse filters are capable of recovering the original or true signal. The second filter shows superiority in terms of convergence, lower computational cost, and lower error due to its optimized parameters. The predictive filter indicates good working accuracy for the signal prediction.
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Zhang, Zilong, and C. Steve Suh. "A Novel Nonlinear Time-Frequency Control Strategy for Underactuated Mechanical System." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10778.

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Abstract In this paper, a novel nonlinear time-frequency control methodology is presented to address the stabilization of an underactuated surface vessel (USV). The wavelet-domain based time-frequency control technique augmented by the adaptive filters and filtered-x least-mean-square algorithm is employed as the primary control framework. A nonlinear three degrees-of-freedom planar dynamic model for the USV with only two available control inputs is considered in the study. The equations of motion are derived based on the Newton’s Second law of motion. By using wavelet transform and filter banks, the proposed nonlinear control algorithm requires no mathematical simplification or linearization of the physical system, thus retaining all the true nonlinear dynamics of the USV model. The presented nonlinear controller consists of two adaptive finite impulse response (FIR) filers that operate on wavelet coefficients: the first one is used to model the dynamic system on-line and provide a priori information in real-time while the second one serves as a feed-forward controller and rejects the uncontrollable input signal based on the first FIR filter. The proposed nonlinear time-frequency controller properly mitigates dynamical deterioration in both the time and frequency domains and regulates the system response with the desired stability. Numerical simulations are performed in MATLAB Simulink and the results validate the effectiveness of the proposed nonlinear time-frequency control approach.
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Fang, Haowen, Amar Shrestha, Ziyi Zhao, and Qinru Qiu. "Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/388.

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The recently discovered spatial-temporal information processing capability of bio-inspired Spiking neural networks (SNN) has enabled some interesting models and applications. However designing large-scale and high-performance model is yet a challenge due to the lack of robust training algorithms. A bio-plausible SNN model with spatial-temporal property is a complex dynamic system. Synapses and neurons behave as filters capable of preserving temporal information. As such neuron dynamics and filter effects are ignored in existing training algorithms, the SNN downgrades into a memoryless system and loses the ability of temporal signal processing. Furthermore, spike timing plays an important role in information representation, but conventional rate-based spike coding models only consider spike trains statistically, and discard information carried by its temporal structures. To address the above issues, and exploit the temporal dynamics of SNNs, we formulate SNN as a network of infinite impulse response (IIR) filters with neuron nonlinearity. We proposed a training algorithm that is capable to learn spatial-temporal patterns by searching for the optimal synapse filter kernels and weights. The proposed model and training algorithm are applied to construct associative memories and classifiers for synthetic and public datasets including MNIST, NMNIST, DVS 128 etc. Their accuracy outperforms state-of-the-art approaches.
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Zuo, Lei, and Samir A. Nayfeh. "Adaptive Least-Mean Square Feed-Forward Control With Actuator Saturation by Direct Minimization." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85494.

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The least-mean squares (LMS) adaptive feedforward algorithm is used widely for vibration and noise cancellation. If reference signals become large enough to saturate that actuators, the filter coefficients in such algorithms can diverge. The leaky LMS method limits the controller effort by augmenting the objective function by a weighted control effort, and is known to attain good performance and avoid growth of filter coefficients for well-chosen weights. We propose an algorithm that seeks to directly minimize the mean-square cost in the presence of saturation. We derive the true stochastic gradient of the cost for systems with saturation with respect to the filter coefficients and obtain an adaptation rule very close to that of the filtered-x algorithm, but in the proposed algorithm, the reference filter is a time-varying modification of the secondary channel. In simulations of an active vibration isolation system with actuator limits subject to random ground vibration, the leaky LMS algorithm attains its best performance with actuation weights small enough to allow significant actuator saturation but large enough to prevent divergence. The proposed algorithm attains performance better that attained by the leaky LMS algorithm, and does not require the selection of weights.
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Kim, Ho-Wuk, and Sang-Kwon Lee. "Adaptive IIR Filter Using Variable Step Size for Active Noise Control Inside a Short Duct." In ASME 2008 Noise Control and Acoustics Division Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/ncad2008-73062.

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FIR filter for a adaptive filter algorithm, is mostly used for an active noise control system. However, FIR filter needs to have more large size of the filter length than it of IIR filter. Therefore, the control system using FIR adaptive filter has slow calculation time. In the active noise control system of the short duct, the reference signal can be affected by the output signal, so IIR filter for ARMA system can be more suitable for the active noise control of the short duct than FIR filter for MA system. In this paper, the recursive LMS filter, which is adaptive IIR filter, is applicated for the active noise control inside the short duct. For faster convergence and more accurate control, a variable step size algorithm is introduced for this recursive LMS filter (R-VSSLMS filter). Using this algorithm and considering the secondary path, the filtered-u R-VSSLMS is conducted successfully on the real experiment in the short duct. The performance of the active control using the filtered-u R-VSSLMS filter, is compared with the performance of the active control using a filtered-x LMS filter.
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Sahay, Chittaranjan, Suhash Ghosh, Joseph Daniel Premkumar, and Siva Pooja Ramachandran. "Effect of Filter Type and Filter Size on Roundness/Circularity Measurement Using Different Mathematical Algorithms." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23575.

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Abstract In the manufacturing industry, it is almost inconceivable to produce a rotating component without a minimal amount of roundness tolerance. The importance of studying roundness form deviations of circular and cylindrical features is to avoid the excessive lateral or axial runout deviations of the rotating and reciprocating parts during dynamic operations. Considering the precision that industries require now and will require in the future, the authors of this article have chosen roundness (also called circularity per ASME Standards) as the measurable parameter. In order to arrive at precise results, the roundness of a near-to-perfect cylinder is measured on an accurate spindle and turn-table type measuring instrument. Roundness profile, when measured, can be filtered in various ways to reduce or eliminate unwanted details, with a cut-off value set in terms of undulations per revolution (UPR), which gives valuable information about how the component may function, under specific conditions. Looking at real-life roundness graphs it is clear that information exists in the data at different frequencies. A classic example is ovality, which indicates an irregularity that occurs two times in one complete revolution. The workpiece would be said to have two lobes or two UPR. Multiple lobes may be present on a component, a condition contributing to either problems of fit with mating components or part functionality. Additionally, usage of recommended or generalized filter, yields data that approximately lies in the range of acceptability. Thus, there is a strong need to thoroughly understand the effect of filter size and type on roundness (form error for fit) and part functionality. Many published articles have investigated novel filters to accurately and efficiently calculate roundness. However, no work was found in literature that would present the filter size and type selection criteria and correlate it with roundness depending on mathematical method of calculating roundness and further to part functionality. This paper focusses on the investigation of filter type and size effect on roundness based on different mathematical methods of roundness error calculations. By varying parameters like the filter type (Gaussian 50%, 75% and RC Filters), the filter sizes (1 through 500 UPR) and the methods of measuring the roundness — (Least Squares Circle (LSC), Minimum Circumscribed Circle (MCC), Maximum Inscribed Circle (MIC) and Minimum Zone Circles or Separation (MZC or MZS)), roundness at different heights of the workpiece is evaluated. A clear trend is observed from the results, which can further help one to choose filters and their respective sizes for the respective design intent or the application in question.
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Elasha, Faris, Cristobal Ruiz-Carcel, and David Mba. "Bearing Natural Degradation Detection in a Gearbox: A Comparative Study of the Effectiveness of Adaptive Filter Algorithms and Spectral Kurtosis." In ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/esda2014-20244.

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Bearing faults detection at the earliest stages is vital in avoiding future catastrophic failures. Many traditional techniques have been established and utilized in detecting bearing faults, though, these diagnostic techniques are not always successful when the bearing faults take place in gearboxes where the vibration signal is complex; under such circumstances it may be necessary to separate the bearing signal from the complex signal. The objective of this paper is to assess the effectiveness of an adaptive filter algorithms compared to a Spectral Kurtosis (SK) algorithm in diagnosing a bearing defects in a gearbox. Two adaptive filters have been used for the purpose of bearing signal separation, these algorithms were Least Mean Square (LMS) and Fast Block LMS (FBLMS) algorithms. These algorithms were applied to identify a bearing defects in a gearbox employed for an aircraft control system for which endurance tests were performed. The results show that the LMS algorithm is capable of detecting the bearing fault earlier in comparison to the other algorithms.
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Tharayil, Marina, and Andrew Alleyne. "Optimal Time-Varying ILC Design to Monotonically Minimize Converged Error." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-79186.

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This paper presents a design method for Iterative Learning Control (ILC) algorithms using time-varying Q-filters. The design of an optimal bandwidth profile for a given plant model is formulated as a constrained minimization problem. The resultant time-varying ILC algorithm generates the lowest converged error norm possible while guaranteeing monotonic convergence. The time-varying ILC background, problem setup to optimize the time-varying Q-filter bandwidth, as well as results obtained using computational methods are presented. A simulation example is used to demonstrate the potential benefits of the algorithm in comparison with LTI ILC. Lastly, experimental validation is provided by application of the ILC algorithm developed here on a Microscale Robotic Deposition system for precision motion control.
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Mosquera-Lopez, Clara, and Daniel Pack. "Comparative Out-of-Sequence Estimation Techniques for Multi-Sensor Target Tracking." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-5863.

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In this paper, performance comparisons are carried out between two out-of-sequence estimation filtering techniques based on the principles of the Extended Kalman Filter (EKF) and the Sigma-point Kalman filter (SPKF), in a mobile platform tracking application where distributed radars are used to estimate both linear and highly nonlinear movements of an aircraft. Two scenarios were considered: 1) aircraft movements fit a white noise acceleration model; and 2) aircraft movement follows a coordinated turn model with unknown turn rate. In addition, we evaluate the individual performance of the out-of-order filters against the ideal cases obtained by running the EKF and SPKF with reordered measurements in a chronological sequence. Simulation results show that the algorithms used for dealing with out-of-sequence measurements closely resemble the performance of the non-out-of-order filters. In terms of estimation accuracy, the out-of-order algorithm based on the SPKF outperforms the one based on the EKF when a highly nonlinear aircraft movement is observed. For nearly linear systems, there is not a significant difference between the two approaches.
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Reports on the topic "Filter Algorithmus"

1

Abramson, Mark A., Charles Audet, Jr Dennis, and J. E. Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems. Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada445031.

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Liu, Xinmin, Zongli Lin, and Scott Acton. A New Particle Filter Based Algorithm for Image Tracking. Fort Belvoir, VA: Defense Technical Information Center, July 2008. http://dx.doi.org/10.21236/ada501159.

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Hock, Melinda. Kalman Filter Predictor and Initialization Algorithm for PRI Tracking. Fort Belvoir, VA: Defense Technical Information Center, June 1998. http://dx.doi.org/10.21236/ada349258.

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Darling, R. W. Geometrically Intrinsic Nonlinear Recursive Filers I: Algorithms. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada436451.

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Berney, Ernest, Andrew Ward, and Naveen Ganesh. First generation automated assessment of airfield damage using LiDAR point clouds. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/40042.

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This research developed an automated software technique for identifying type, size, and location of man-made airfield damage including craters, spalls, and camouflets from a digitized three-dimensional point cloud of the airfield surface. Point clouds were initially generated from Light Detection and Ranging (LiDAR) sensors mounted on elevated lifts to simulate aerial data collection and, later, an actual unmanned aerial system. LiDAR data provided a high-resolution, globally positioned, and dimensionally scaled point cloud exported in a LAS file format that was automatically retrieved and processed using volumetric detection algorithms developed in the MATLAB software environment. Developed MATLAB algorithms used a three-stage filling technique to identify the boundaries of craters first, then spalls, then camouflets, and scaled their sizes based on the greatest pointwise extents. All pavement damages and their locations were saved as shapefiles and uploaded into the GeoExPT processing environment for visualization and quality control. This technique requires no user input between data collection and GeoExPT visualization, allowing for a completely automated software analysis with all filters and data processing hidden from the user.
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Maschal, Jr, Young Robert A., Reynolds S. S., Krapels Joe, Fanning Keith, Corbin Jonathan, and Ted. Review of Bayer Pattern Color Filter Array (CFA) Demosaicing with New Quality Assessment Algorithms. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada513752.

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Fournier, Sean Donovan, Sonoya Toyoko Shanks, John M. McCulloch, Luis Miguel Valdivia, and Rose T. Preston. The iSERIES radon progeny compensation algorithm and its application to air filters. Office of Scientific and Technical Information (OSTI), October 2012. http://dx.doi.org/10.2172/1055933.

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Abramson, Mark A. Mixed Variable Optimization of a Load-Bearing Thermal Insulation System Using a Filter Pattern Search Algorithm. Fort Belvoir, VA: Defense Technical Information Center, May 2003. http://dx.doi.org/10.21236/ada451457.

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Kanagavel, Rameshkumar, and Indragandhi Vairavasundaram. FPGA Implementation and Investigation of Hybrid Artificial Bee Colony Algorithm-based Single Phase Shunt Active Filter. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, May 2020. http://dx.doi.org/10.7546/crabs.2020.05.13.

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Amela, R., Q. Ayoul-Guilmard, S. Ganesh, R. Tosi, R. Badia, F. Nobile, R. Rossi, and C. Soriano. D5.2 Release of ExaQUte MLMC Python engine. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.024.

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In this deliverable, the ExaQUte xmc library is introduced. This report is meant to serve as a supplement to the publicly release of the library. In the following sections, the ExaQUte xmc library is described along with its current and future capabilities. The structure of the library, along with its dynamic import mechanism, are described using samples of code. The algorithms behind the example files supplied with the public release are explained in detail as well.
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