Journal articles: '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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Mishra, Akshansh. "Machine Learning Algorithm for Surface Quality Analysis of Friction Stir Welded Joint." Strojnícky časopis - Journal of Mechanical Engineering 70, no. 2 (November 1, 2020): 11–20. http://dx.doi.org/10.2478/scjme-2020-0016.

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AbstractThe Friction Stir Welding process usually produces weld members of good quality compared to composite weld made with a standard welding process. However, there is a possibility of the formation of various defects if the input parameters are not properly selected. In the recent case study, an image-based feature recognition system using the Fourier conversion method which is a computer visual recognition tool is developed. Five types of filters like Ideal Filter, Butterworth Filter, Low Filter, Gaussian Filter, and High Pass Filter. The results showed that the high pass filter has more ability to detect surface defects compared to the other four filters. It has also been observed that the Ideal filter has a lot of distortions compared to the Gaussian Filter and the Butterworth Filter.

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Abubakar, Yusuf. "DEVELOPMENT OF SOFTWARE FOR QUANTUM VOLTAGE SYNTHESISER." FUDMA JOURNAL OF SCIENCES 4, no. 3 (September 11, 2020): 17–25. http://dx.doi.org/10.33003/fjs-2020-0403-167.

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Signal analysis is a wide area of research, which received considerable attention due to its numerous fields of application. The impact of these fields in technological advancement cannot be overemphasized. No matter how good a signal is acquired, it can still contain some unwanted components (noise) that is capable of undermining its integrity. This work synthesizes signal from a delta-sigma system by designing digital filters LabVIEW program. The designed lowpass and bandpass filters were examined in addition to different filter design algorithms. Based on the analysis, Dolph-chebyshev and Kaiser window filters provide excellent filtering by blocking quantization noise to up to -40dB for fixed point design and, -60dB for floating point. Despite issues with windowing in filter design, these two algorithms seem to work well with this type of signal. Additionally, this design can be optimised by pushing the filter to its limit.

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Nerger, Lars, Tijana Janjić, Jens Schröter, and Wolfgang Hiller. "A Unification of Ensemble Square Root Kalman Filters." Monthly Weather Review 140, no. 7 (July 1, 2012): 2335–45. http://dx.doi.org/10.1175/mwr-d-11-00102.1.

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Abstract In recent years, several ensemble-based Kalman filter algorithms have been developed that have been classified as ensemble square root Kalman filters. Parallel to this development, the singular “evolutive” interpolated Kalman (SEIK) filter has been introduced and applied in several studies. Some publications note that the SEIK filter is an ensemble Kalman filter or even an ensemble square root Kalman filter. This study examines the relation of the SEIK filter to ensemble square root filters in detail. It shows that the SEIK filter is indeed an ensemble square root Kalman filter. Furthermore, a variant of the SEIK filter, the error subspace transform Kalman filter (ESTKF), is presented that results in identical ensemble transformations to those of the ensemble transform Kalman filter (ETKF), while having a slightly lower computational cost. Numerical experiments are conducted to compare the performance of three filters (SEIK, ETKF, and ESTKF) using deterministic and random ensemble transformations. The results show better performance for the ETKF and ESTKF methods over the SEIK filter as long as this filter is not applied with a symmetric square root. The findings unify the separate developments that have been performed for the SEIK filter and the other ensemble square root Kalman filters.

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Bui, Ngoc Ha, Tien Hung Bui, Thuy Duong Tran, Kim Tuan Tran, and Ngoc Toan Tran. "Evaluation of the effect of filters on reconstructed image quality from cone beam CT system." Nuclear Science and Technology 11, no. 1 (March 15, 2021): 35–47. http://dx.doi.org/10.53747/jnst.v11i1.130.

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: 3D Filtered Back Projection (FBP) is a three-dimensional reconstruction algorithm usually used in Cone Beam Computed Tomography (CBCT) system. FBP is one of the most popular algorithms due to its reconstruction is fast while quality of the result is acceptable. It can also handle a more considerable amount of data with same computer performance with other algorithms. However, the quality of a reconstructed image by the FBP algorithm strongly depends on spatial filters and denoising filters applied to projections. In this paper an evaluation of the reconstructed image quality of the CBCT system by using different denoising filters and spatial filters to find out the best filters for the CBCT system is performed. The result shows that, there is a significantly decrease of the noise of projection with the combination of Median and Gaussian filters. The reconstructed image has high resolution with Cosine filter and becomes more sharpen with Hanning filter.

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Pichardo, Eduardo, Ángel Vázquez, Esteban R. Anides, Juan C. Sánchez, Hector Perez, Juan G. Avalos, and Giovanny Sánchez. "A Dual Adaptive Filter Spike-Based Hardware Architecture for Implementation of a New Active Noise Control Structure." Electronics 10, no. 16 (August 12, 2021): 1945. http://dx.doi.org/10.3390/electronics10161945.

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Presently, the technology development trend of active noise control (ANC) systems is focused on implementing advanced adaptive filters in resource-constrained electronic appliances. Recently, several authors have proved that the use of two adaptive filter algorithms significantly improves the overall adaptive filter performance. However, the computational cost of these approaches is significantly increased since they use two filters simultaneously. Consequently, these filters cannot be implemented in these devices. To solve this problem, we propose a new ANC structure with switching selection based on filtered-x normalized least mean square (FxNLMS) and filtered-x sign least mean square (FxSLMS) algorithms to reduce the computational cost of the ANC system. The improvement of this factor has allowed us to introduce for the first time an advanced spike-based architecture, which can perform dual filter operations using dynamic routing, to be used in real ANC applications. The results have demonstrated that the computational cost of the proposed dual D-FxNLMS/SLMS algorithm is lower compared with previously reported solutions.

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Dambrauskas, Algirdas, and Vytautas Rinkevičius. "Variable Structure Filter Algorithmic Synthesis." Solid State Phenomena 113 (June 2006): 79–84. http://dx.doi.org/10.4028/www.scientific.net/ssp.113.79.

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The aim of the work is to create and refine methods of algorithmic filter synthesis allowing for the designing of variable structure filters in cases when statistical characteristics of effective signal and interference – non-stationary stochastic processes – are unknown and the application of classic synthesis methods, e.g. Kalman-Busy method, is impossible. The paper presents the basics of an algorithmic variable structure filter synthesis, the essence of which is the formulation of the filter synthesis task in the form of searching optimization and its solution with application of simplex search methods. An example of algorithmic variable structure filter synthesis is presented. Parameters of a variable structure filter transfer function found by algorithmic method correspond to theoretical parameters calculated on the basis of statistical characteristics of input signals.

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Zhou, Hongbo, and George A. McMechan. "Parallel Butterworth and Chebyshev dip filters with applications to 3-D seismic migration." GEOPHYSICS 64, no. 5 (September 1999): 1573–78. http://dx.doi.org/10.1190/1.1444661.

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Dip filtering is a necessary part of accurate frequency‐space domain migration, so design and application of reliable and efficient filters are of practical as well as theoretical importance. Frequency‐space domain dip filters are implemented using Butterworth and Chebyshev algorithms. By transforming the product terms of the filter transfer function into summations, a cascaded (serial) Butterworth or Chebyshev dip filter can be made parallel, which improves computational efficiency. For a given order of filter, the cost of the Butterworth and Chebyshev filters is the same. However, the Chebyshev filter has a sharper transition zone than that of a Butterworth filter with the same order, which makes it more effective for phase compensation than a Butterworth filter, but at the expense of some wavenumber‐dependent amplitude ripples. Both implementations have been incorporated into 3-D one‐way frequency‐space depth migration for evanescent energy removal and for phase compensation of splitting errors; a single filter achieves both goals.

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Michalski, Jacek, Piotr Kozierski, and Joanna Zietkiewicz. "Double hybrid Kalman filtering for state estimation of dynamical systems." ITM Web of Conferences 28 (2019): 01051. http://dx.doi.org/10.1051/itmconf/20192801051.

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In this paper authors present a new approaches to the hybrid Kalman filtering and modified hybrid Kalman filtering, with the changed order of methods inside (Unscented Kalman Filter and Extended Kalman Filter). For these algorithms, the modification based on double use of Hybrid Kalman Filters (Excented and Unscented) has been proposed. This new modification has been checked for Hybrid Kalman Particle Filters too, for the variable number of particles. Based on the obtained results, one can see that duplication of hybrid filters can improve the estimation quality.

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Li, Qi Rui, Ming Ming Jiang, Bing Luo, Xiao Ping Hu, and Kang Hua Tang. "Design of Fast Second-Order IIR Low-Pass Filter Based on Parameter Optimization." Applied Mechanics and Materials 644-650 (September 2014): 4382–86. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.4382.

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Second-order IIR low-pass filter is widely used in digital signal processing. A fast filter algorithm without multiplication is proposed for it in this paper. A configuration method for the filter coefficient of fast algorithm is put forward, considering the characteristic of second-order IIR low-pass filter coefficient and the filter’s mathematical model. A performance analysis of fast second-order IIR low-pass filter without multiplication is shown in the paper, and the performance of the fast filter is shown by example using MATLAB simulation. What’s more, the algorithm’s rapidity is verified by an implementation of the filter on FPGA, which turns out that fast filtering algorithm takes only 54.7% of common algorithm’s operation time to realize the same filer function.

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Radonjic, Aleksandar, and Jelena Certic. "Analysis of half-band approximately linear phase IIR filter realization structure in MATLAB." Facta universitatis - series: Electronics and Energetics 28, no. 4 (2015): 611–23. http://dx.doi.org/10.2298/fuee1504611r.

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In this paper a detailed analysis of an atypical filter structure in MATLAB Filter Design and Analysis (FDA) Tool is presented. As an example of atypical filter structure, the IIR half-band filter with approximately linear phase realized as a parallel connection of two all-pass branches was examined. We compare two types of those filters obtained by two different design algorithms. FDA tool was used for the experiment because different effects of the fixed point implementation can be simulated easily. One of the goals of this paper was to compare results obtained by two different design algorithms. In addition, different realizations of the filter structure based on the parallel connection of two all-pass branches were examined.

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BURNIKEL, CHRISTOPH, STEFAN FUNKE, and MICHAEL SEEL. "EXACT GEOMETRIC COMPUTATION USING CASCADING." International Journal of Computational Geometry & Applications 11, no. 03 (June 2001): 245–66. http://dx.doi.org/10.1142/s0218195901000493.

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In this paper we talk about a new efficient numerical approach to deal with inaccuracy when implementing geometric algorithms. Using various floating-point filters together with arbitrary precision packages, we develop an easy-to-use expression compiler called EXPCOMP. EXPCOMP supports all common operations [Formula: see text]. Applying a new semi-static filter, EXPCOMP combines the speed of static filters with the power of dynamic filters. The filter stages deal with all kinds of floating-point exceptions, including underflow. The resulting programs show a very good runtime behaviour.

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Górski, Paweł, and Leszek Morzyński. "Active Noise Reduction Algorithm Based on NOTCH Filter and Genetic Algorithm." Archives of Acoustics 38, no. 2 (June 1, 2013): 185–90. http://dx.doi.org/10.2478/aoa-2013-0021.

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Abstract Application of active noise reduction (ANR) systems in hearing protectors requires the use of control algorithms to ensure stability of the ANR system and at the same time highly effective active noise reduction. A control algorithm based on NOTCH filters is an example of solutions that meet these criteria. Their disadvantage is operation over a narrow frequency band and a need for prior determination of frequencies to be reduced. This paper presents a solution of the ANR system for hearing protectors which is controlled with the use of modified NOTCH filters with parameters determined by a genetic algorithm. Application of a genetic algorithm allows to change the NOTCH filter reference signal frequency, and thus, adapt the filter to the reduced signal frequency.

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Yun, Youngsun, Ho Yun, Doyoon Kim, and Changdon Kee. "A Gaussian Sum Filter Approach for DGNSS Integrity Monitoring." Journal of Navigation 61, no. 4 (October 2008): 687–703. http://dx.doi.org/10.1017/s0373463308004906.

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With conventional snapshot RAIM algorithms, it is difficult to detect small errors and simultaneous multiple faults. Assuming that we know the system dynamics, filtering algorithms, such as the Kalman filter, can provide better integrity-monitoring performance than the snapshot algorithms because the filter reduces the noise level of measurements. However, because the Kalman filter presumes that measurement noise and disturbance follow the Gaussian distribution, its performance might degrade if the assumption is wrong. To address this problem, we propose a fault detection and exclusion algorithm using Gaussian sum filters. Because GNSS measurement noise does not follow the Gaussian distribution perfectly, the Gaussian sum filter can estimate the posterior distribution more accurately; therefore it has better integrity-monitoring performance. This paper describes the detailed algorithms and shows simulation results to evaluate the integrity-monitoring performance of the algorithms. The proposed algorithms detect about 30% smaller faults and generate 35% lower protection levels than the conventional methods. The results show that the proposed algorithms can provide better accuracy and availability performance.

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Alhafadhi, Liqaa, Jiashen Teh, Ching-Ming Lai, and Mohamed Salem. "Predictive Adaptive Filter for Reducing Total Harmonics Distortion in PV Systems." Energies 13, no. 12 (June 26, 2020): 3286. http://dx.doi.org/10.3390/en13123286.

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This paper presents a new method for reducing the total harmonic distortion (THD) of photovoltaic (PV) systems by using an adaptive filter based on a predictive model. Instead of reducing the produced THD at each stage of the PV system, a one-step process is implemented at the end stage. The connection topology of the adaptive filter is similar to normal active and passive filters. The main difference is its ability to adjust the filtering coefficients while others cannot. The proposed method is applied to a single-phase standalone PV system by adopting least mean square (LMS), normalized LMS (NLMS) and leaky LMS algorithms to verify the validity of the proposed method. Various values of filter length and step size are evaluated, and results indicate that the proposed method can reduce THD in the current signal of the PV system significantly by using all of the mentioned algorithms. Different step sizes and filter lengths directly influence the effectiveness of the THD reduction, with small step sizes and long filters being the most effective. Amongst the algorithms, NLMS reduces THD the most, and LMS reaches the peak current value the fastest.

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Hanea, R. G., G. J. M. Velders, A. J. Segers, M. Verlaan, and A. W. Heemink. "A Hybrid Kalman Filter Algorithm for Large-Scale Atmospheric Chemistry Data Assimilation." Monthly Weather Review 135, no. 1 (January 1, 2007): 140–51. http://dx.doi.org/10.1175/mwr3269.1.

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Abstract In the past, a number of algorithms have been introduced to solve data assimilation problems for large-scale applications. Here, several Kalman filters, coupled to the European Operational Smog (EUROS) atmospheric chemistry transport model, are used to estimate the ozone concentrations in the boundary layer above Europe. Two Kalman filter algorithms, the reduced-rank square root (RRSQRT) and the ensemble Kalman filter (EnKF), were implemented in a prior study. To combine the best features of these two filters, a hybrid filter was constructed by making use of the reduced-rank approximation of the covariance matrix as a variance reducer for the EnKF. This hybrid algorithm, complementary orthogonal subspace filter for efficient ensembles (COFFEE), is coupled to the EUROS model. The performance of all algorithms is compared in terms of residual errors and number of EUROS model evaluations. The COFFEE results score somewhere between the EnKF and RRSQRT results for less than approximately 30 model evaluations. For more than approximately 30 model evaluations, the COFFEE results are, in all cases, better than the EnKF and RRSQRT results. The results of the COFFEE simulations with more than about 60 model evaluations proved to be significantly better than all the EnKF and RRSQRT simulations (even better than those with 100 and 200 modes or ensemble members). The performance of both the EnKF- and RRSQRT-type filters is affected by the nonlinear properties of the model and observation operator, because both rely on linearization to some extent. To further study this aspect, several measures of nonlinearity were calculated and linked with the performance of these algorithms.

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Romanovas, Michailas, Lasse Klingbeil, Martin Traechtler, and Yiannos Manoli. "APPLICATION OF FRACTIONAL SENSOR FUSION ALGORITHMS FOR INERTIAL MEMS SENSING." Mathematical Modelling and Analysis 14, no. 2 (June 30, 2009): 199–209. http://dx.doi.org/10.3846/1392-6292.2009.14.199-209.

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The work presents an extension of the conventional Kalman filtering concept for systems of fractional order (FOS). Modifications are introduced using the Grünwald‐Letnikov (GL) definition of the fractional derivative (FD) and corresponding truncation of the history length. Two versions of the fractional Kalman filter (FKF) are shown, where the FD is calculated directly or by augmenting the state vector with the estimate of the FD. The filters are compared to conventional integer order (IO) Position (P‐KF) and Position‐Velocity (PV‐KF) Kalman filters as well as to an adaptive Interacting Multiple‐Model Kalman Filter (IMM‐KF). The performance of the filters is assessed based on a hand and a head motion data set. The feasibility of the given approach is shown.

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Ali, Zain, Bharat Lal Harijan, Tayab Din Memon, Nazmus Naf, and Ubed-u.-Rahman Memon. "Digital FIR Filter Design by PSO and its variants Attractive and Repulsive PSO(ARPSO) & Craziness based PSO(CRPSO)." International Journal of Recent Technology and Engineering 9, no. 6 (March 30, 2021): 136–41. http://dx.doi.org/10.35940/ijrte.f5515.039621.

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Digital filters play a major role in signal processing that are employed in many applications such as in control systems, audio or video processing systems, noise reduction applications and different systems for communication. In this regard, FIR filters are employed because of frequency stability and linearity in their phase response. FIR filter design requires multi-modal optimization problems. Therefore, PSO (Particle Swarm Optimization) algorithm and its variants are more adaptable techniques based upon particles’ population in the search space and a great option for designing FIR filter. PSO and its different variants improve the solution characteristic by providing a unique approach for updating the velocity and position of the swarm. An optimized set of filter coefficient is produced by PSO and its variant algorithms which gives the optimized results in passband and stopband. In this research paper, Digital FIR filter is effectively designed by using PSO Algorithm and its two variants ARPSO and CRPSO in MATLAB. The outcomes prove that the filter design technique using CRPSO is better than filter design by PM algorithm. PSO and ARPSO Algorithms in the context of frequency spectrum and RMS error.

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Stosic, Biljana. "Coefficient quantization effects on new filters based on Chebyshev fourth-kind polynomials." Facta universitatis - series: Electronics and Energetics 34, no. 2 (2021): 291–305. http://dx.doi.org/10.2298/fuee2102291s.

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The aim of this paper is to construct non-recursive filters, extensively used type of digital filters in digital signal processing applications, based on Chebyshev orthogonal polynomials. The paper proposes the use of the fourth-kind Chebyshev polynomials as functions in generating new filters. In this kind, low-pass filters with linear phase responses are obtained. Comprenhansive study of the frequency response characteristics of the generated filter functions is presented. The effects of coefficient quantization as one type of quantization that influences a filter characteristic are investigated here also. The quantized-coefficient errors are considered based on the number of bits and the implementation algorithms.

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Lu, Feng, Yafan Wang, Jinquan Huang, Yihuan Huang, and Xiaojie Qiu. "Fusing unscented Kalman filter for performance monitoring and fault accommodation in gas turbine." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 3 (December 12, 2016): 556–70. http://dx.doi.org/10.1177/0954410016682269.

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The Kalman filter is widely utilized for gas turbine health monitoring due to its simplicity, robustness, and suitability for real-time implementations. The most common Kalman filter for linear systems is linearized Kalman filter, and for nonlinear systems are extended Kalman filter and unscented Kalman filter. These algorithms have proven their capabilities to estimate gas turbine performance variations with a good accuracy, and the studies are done provided that all sensor measurements are available. In this paper, a nonlinear fusion approach with consistent diagnostic mechanism based on unscented Kalman filter is proposed, especially for gas turbine performance monitoring in the case of sensor failure. The architecture of fusion method comprises a set of local unscented Kalman filters and an information mixer. The local unscented Kalman filters are utilized to estimate health parameters of various component combinations, and the results are then transferred to the mixer for the integrated estimation of global health state in fusion structure. The consistent fault diagnosis and isolation logic is designed based on the fusion architecture and combined with the fusing unscented Kalman filter, called an improved fusing unscented Kalman filter. A systematic comparison of the generic linearized Kalman filter, extended Kalman filter, and unscented Kalman filter to their fusion filter kinds is presented for engine health estimation of gradual deterioration and abrupt fault. The studies show that the fusing unscented Kalman filter evidently outperforms the fusing linearized Kalman filter and fusing extended Kalman filter, while the fusing Kalman filters have slightly better estimation accuracy than the basic Kalman filters. In addition, the proposed methodology can reach the reliable performance monitoring with measurement uncertainty while the conventional Kalman filters collapse.

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Su, Te-Jen, Tsang-Chi Yang, Wen-Pin Tsai, and Jia-Wei Liu. "Design Two-Dimensional IIR Filters Based on Clonal Selection Algorithm with Singular Value Decomposition." Research Letters in Signal Processing 2007 (2007): 1–5. http://dx.doi.org/10.1155/2007/32081.

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In this letter, clonal selection algorithm (CSA) with singular value decomposition (SVD) method is investigated for the realization of two-dimentional (2D) infinite-impulse response (IIR) filters with arbitrary magnitude responses. The CSA is applied to optimize the sampled frequencies of transition band of digital filters, then producing a planar response matrix of a 2D IIR digital filter. By using the SVD, 2D magnitude specifications can be decomposed into a pair of 1D filters, and thus the problem of designing a 2D digital filter can be reduced to the one of designing a pair of 1D digital filters or even only one 1D digital filter. The stimulation results show the proposed method has the better performance of the minimum attenuation between the passband and stopband.

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Li, Xiao Zhou. "A Framework Design of Spatial Gamut Mapping." Advanced Materials Research 468-471 (February 2012): 628–32. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.628.

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The common filters used in spatial gamut mapping algorithms were studied in this paper which included Gaussian filter and bilateral filter based on spatial gamut mapping theory. And one framework of spatial gamut mapping oriented to digital printing was designed which combined the printing image characteristics and reproduction requirements. The framework combined printing image processing technique and gamut mapping technique and the results help to choose or develop better spatial gamut mapping algorithms oriented to digital printing.

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FONTAINE, MARC, STEFAN BURKHARDT, and JUHA KÄRKKÄINEN. "BDD-BASED ANALYSIS OF GAPPED q-GRAM FILTERS." International Journal of Foundations of Computer Science 16, no. 06 (December 2005): 1121–34. http://dx.doi.org/10.1142/s0129054105003698.

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Recently, there has been a surge of interest in gapped q-gram filters for approximate string matching. Important design parameters for filters are for example the value of q, the filter-threshold and in particular the shape (aka seed) of the filter. A good choice of parameters can improve the performance of a q-gram filter by orders of magnitude and optimizing these parameters is a nontrivial combinatorial problem. We describe a new method for analyzing gapped q-gram filters. This method is simple and generic. It applies to a variety of filters, overcomes many restrictions that are present in existing algorithms and can easily be extended to new filter variants. To implement our approach, we use an extended version of BDDs (Binary Decision Diagrams), a data structure that efficiently represents sets of bit-strings. In a second step, we define a new class of multi-shape filters and analyze these filters with the BDD-based approach. Experiments show that multi-shape filters can outperform the best single-shape filters, which are currently in use, in many aspects. The BDD-based algorithm is crucial for the design and analysis of these new and better multi-shape filters. Our results apply to the k-mismatches problem, i.e. approximate string matching with Hamming distance.

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Khoury, J., Peter D. Gianino, and Charles L. Woods. "Optimal correlation filter algorithms for holographically stored multiplexed filters." Optics Communications 168, no. 5-6 (September 1999): 337–42. http://dx.doi.org/10.1016/s0030-4018(99)00369-7.

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Siwczyński, M., A. Drwal, and S. Żaba. "The digital function filters – algorithms and applications." Bulletin of the Polish Academy of Sciences: Technical Sciences 61, no. 2 (June 1, 2013): 371–77. http://dx.doi.org/10.2478/bpasts-2013-0036.

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Abstract The simple digital filters are not sufficient for digital modeling of systems with distributed parameters. It is necessary to apply more complex digital filters. In this work, a set of filters, called the digital function filters, is proposed. It consists of digital filters, which are obtained from causal and stable filters through some function transformation. In this paper, for several basic functions: exponential, logarithm, square root and the real power of input filter, the recursive algorithms of the digital function filters have been determined The digital function filters of exponential type can be obtained from direct recursive formulas. Whereas, the other function filters, such as the logarithm, the square root and the real power, require using the implicit recursive formulas. Some applications of the digital function filters for the analysis and synthesis of systems with lumped and distributed parameters (a long line, phase shifters, infinite ladder circuits) are given as well.

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Maciążek, Marcin, Dariusz Grabowski, and Marian Pasko. "Genetic and combinatorial algorithms for optimal sizing and placement of active power filters." International Journal of Applied Mathematics and Computer Science 25, no. 2 (June 1, 2015): 269–79. http://dx.doi.org/10.1515/amcs-2015-0021.

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Abstract The paper deals with cost effective compensator placement and sizing. It becomes one of the most important problems in contemporary electrical networks, in which voltage and current waveform distortions increase year-by-year reaching or even exceeding limit values. The suppression of distortions could be carried out by means of three types of compensators, i.e., passive filters, active power filters and hybrid filters. So far, passive filters have been more popular mainly because of economic reasons, but active and hybrid filters have some advantages which should cause their wider application in the near future. Active power filter placement and sizing could be regarded as an optimization problem. A few objective functions have been proposed for this problem. In this paper we compare solutions obtained by means of combinatorial and genetic approaches. The theoretical discussion is followed by examples of active power filter placement and sizing

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González-Hidalgo, Manuel, Sebastia Massanet, Arnau Mir, and Daniel Ruiz-Aguilera. "Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density." Applied Sciences 11, no. 2 (January 8, 2021): 560. http://dx.doi.org/10.3390/app11020560.

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Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any noise density from 5% to 98%. A statistical analysis based on some objective restoration measures supports that this filter surpasses several state-of-the-art filters for most of the noise levels considered in the comparison experiments.

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Gallegos-Funes, F., J. Martínez-Valdés, R. Cruz-Santiago, and J. López-Bonilla. "Wavelet Order Statistics Filters for Image Denoising." Journal of Scientific Research 1, no. 2 (April 22, 2009): 248–57. http://dx.doi.org/10.3329/jsr.v1i2.2311.

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This paper presents the wavelet order statistics filters for the removal of impulsive and speckle noise in color image applications. The proposed filtering scheme is defined as two filters in the wavelet domain to conform to the structure of a general filter that can be modified in some headings. The first filter is based on redundancy of approaches and the second one is the wavelet domain iterative center weighted median algorithm. With the structure of the proposed filter different implementations for the estimation of the noisy sample are carried out using different order statistics algorithms that by their good performance can be beneficial in color image processing applications. Keywords: Wavelet domain; Order statistics filters. © 2009 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.DOI: 10.3329/jsr.v1i2.2311

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González-Hidalgo, Manuel, Sebastia Massanet, Arnau Mir, and Daniel Ruiz-Aguilera. "Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density." Applied Sciences 11, no. 2 (January 8, 2021): 560. http://dx.doi.org/10.3390/app11020560.

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Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any noise density from 5% to 98%. A statistical analysis based on some objective restoration measures supports that this filter surpasses several state-of-the-art filters for most of the noise levels considered in the comparison experiments.

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Petrosian, Ruslan, Vladyslav Chukhov, and Arsen Petrosian. "Development of a method for synthesis the FIR filters with a cascade structure based on genetic algorithm." Technology audit and production reserves 4, no. 2(60) (July 31, 2021): 6–11. http://dx.doi.org/10.15587/2706-5448.2021.237271.

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The object of research is the process of digital signal processing. The subject of research is methods of synthesis of digital filters with a finite impulse response based on a genetic algorithm. Digital filtering is one of the tasks of digital signal processing. FIR filters are always stable and provide a constant group delay. There are various methods for synthesizing digital filters, but they are all aimed at synthesizing filters with a direct structure. One of the most problematic areas of a digital filter with a direct structure in digital processing is the high sensitivity of the filter characteristics to inaccuracies in setting the filter coefficients. Genetic algorithm-based filter synthesis methods use an ideal filter as the approximated filter. This approach has a number of disadvantages: it complicates the search for an optimal solution; computation time increases. The study used random search method, which is the basis of genetic algorithm (used for solving optimization problems); theory of digital filtering in filter analysis; numerical methods for modeling in a Python program. Prepared synthesis method FIR filter with the cascade structure, which is less sensitive to the effect of finite bit width. Computation time was reduced. This is due to the fact that the proposed method searches for the most suitable filter coefficients based on a genetic algorithm and has a number of features, in particular, it is proposed to use a piecewise-linear function as an approximated amplitude-frequency response. This makes it possible to reduce the number of populations of the genetic algorithm when searching for a solution. The synthesis of an FIR filter with a cascade structure based on a genetic algorithm showed that for a 24-order filter it took about 30–40 generations to get the filter parameters close to the optimal values. In comparison with classical methods of filter synthesis, the following advantages are provided: calculations of the coefficients of a filter with a cascade structure directly, the possibility of optimizing coefficients with limited bit depth.

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Malinowski, Marcin, and Janusz Kwiecień. "Study of the Effectiveness of Different Kalman Filtering Methods and Smoothers in Object Tracking Based on Simulation Tests." Reports on Geodesy and Geoinformatics 97, no. 1 (February 3, 2015): 1–22. http://dx.doi.org/10.2478/rgg-2014-0008.

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AbstractIn navigation practice, there are various navigational architecture and integration strategies of measuring instruments that affect the choice of the Kalman filtering algorithm. The analysis of different methods of Kalman filtration and associated smoothers applied in object tracing was made on the grounds of simulation tests of algorithms designed and presented in this paper. EKF (Extended Kalman Filter) filter based on approximation with (jacobians) partial derivations and derivative-free filters like UKF (Unscented Kalman Filter) and CDKF (Central Difference Kalman Filter) were implemented in comparison. For each method of filtration, appropriate smoothers EKS (Extended Kalman Smoother), UKS (Unscented Kalman Smoother) and CDKS (Central Difference Kalman Smoother) were presented as well. Algorithms performance is discussed on the theoretical base and simulation results of two cases are presented.

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Divya, G. Naga, and S. Koteswara Rao. "Application of Sigma Point Particle Filter Method for Passive State Estimation in Underwater." Defence Science Journal 71, no. 4 (July 1, 2021): 507–14. http://dx.doi.org/10.14429/dsj.71.16284.

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Bearings-only tracking (BOT) plays a vital role in underwater surveillance. In BOT, measurement is tangentially related to state of the system. This measurement is also corrupted with noise due to turbulent underwater environment. Hence state estimation process using BOT becomes nonlinear. This necessitates the use of nonlinear filtering algorithms in place of traditional linear filters like Kalman filter. In general, these nonlinear filters utilize the assumption of measurements being corrupted with Gaussian noise for state estimation. The measurements cannot be always corrupted with Gaussian noise because of the highly unstable sea environment. These problems indicate the necessity for development of nonlinear non-Gaussian filters like particle filter (PF) for underwater tracking. However, PF suffers from severe problems like sample degeneracy and impoverishment and also it is tedious to select an appropriate technique for resampling. To overcome these difficulties in PF implementation, the strategy of combining PF with another filter like unscented Kalman filter is proposed for target’s state estimation. The detailed analysis of the same is presented in comparison with other particle filter combinations using the simulation results obtained in Matlab.

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Shen, Zhengwei. "Construction of symmetric fractional over-complete wavelets and applications in image restoration." International Journal of Wavelets, Multiresolution and Information Processing 14, no. 04 (July 2016): 1650020. http://dx.doi.org/10.1142/s021969131650020x.

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In this work, a novel design scheme is proposed for the construction of symmetric fractional over-complete wavelet filter banks. We first provide solutions to the open problem of designing low-pass filters that are symmetric and of minimum-length. We then obtain the high high-pass filters via Toeplitz matrix factorization which is of less computational complexity than existing methods. The resulting filter banks are approximately shift-invariant. The designed filter banks are applied in image restoration that uses an analysis based model solved by split Bregman algorithms. The experiments show the constructed symmetric fractional over-complete wavelet transforms (FOWTs) allow better restoration results than some other wavelet transforms in the literature.

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LIU, XIAOJIAN, and LEONARD T. BRUTON. "PARALLEL COMPUTING IN MULTIDIMENSIONAL RECURSIVE FILTERING." International Journal of High Speed Electronics and Systems 04, no. 02 (June 1993): 219–43. http://dx.doi.org/10.1142/s0129156493000108.

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This paper introduces and generalizes a number of multidimensional (MD) recursive parallel filter algorithms, which are based on the principles of orthogonal and diagonal computing, respectively. Efficient software and hardware implementation methods for the proposed parallel algorithms are presented. In particular, it is shown that systolic array implementations can be achieved for MD parallel filter structures that are locally interconnected and have a critical path of 1 multiplication plus 1 addition. In this way, the proposed parallel filters are easily able to perform real-time processing at video rates.

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Fong, Li Wei. "Decoupled Adaptive Tracking Algorithm for Multi-Sensor Measurement Fusion." Applied Mechanics and Materials 229-231 (November 2012): 1235–38. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1235.

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A decoupled adaptive tracking filter is developed for centralized measurement fusion to track the same maneuvering target to improve the tracking accuracy. The proposed approach consists of a dual-band Kalman filter and a two-category Bayesian classifier. Based upon data compression and decoupling techniques, two parallel decoupled filters are obtained for lessening computation. The Bayesian classification scheme is employed which involves switching between high-level-band filter and low-level-band filter to continuously resist different target maneuver turns. The simulation results are presented which demonstrate the effectiveness of the proposed method.

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Ninković, Darko, and Dragan Olćan. "Genetic algorithm applied to discrete optimization of band-pass microwave filter." Telfor Journal 13, no. 1 (2021): 19–24. http://dx.doi.org/10.5937/telfor2101019n.

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We propose a design approach for band-pass microwave filters based on optimization of discrete-valued parameters of filters using an implementation of (1 + (l, l)) genetic algorithm. If the filter is made of SMD components then only discrete values are allowed. The proposed design approach yields a solution with feasible components values in the end, without further need for tuning and adjustments of component values that is needed in the case when real numbers are used during optimization. The optimization setup is run for 20 times and obtained (suboptimal) solutions are presented. One of the best optimized solutions of a band-pass filter is chosen for further analysis. The found filter design is verified using a circuit solver including the yield analysis, 3D electromagnetic simulations and by measurements of the manufactured prototype. The presented results as well as the optimization run-time show that the proposed approach based on discrete optimization can be used to design microwave filters.

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Kaplun, Dmitry, Denis Butusov, Valerii Ostrovskii, Alexander Veligosha, and Vyacheslav Gulvanskii. "Optimization of the FIR Filter Structure in Finite Residue Field Algebra." Electronics 7, no. 12 (December 2, 2018): 372. http://dx.doi.org/10.3390/electronics7120372.

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This paper introduces a method for optimizing non-recursive filtering algorithms. A mathematical model of a non-recursive digital filter is proposed and a performance estimation is given. A method for optimizing the structural implementation of the modular digital filter is described. The essence of the optimization is that by using the property of the residue ring and the properties of the symmetric impulse response of the filter, it is possible to obtain a filter having almost a half the length of the impulse response compared to the traditional modular filter. A difference equation is given by calculating the output sample of modules p1 … pn in the modified modular digital filter. The performance of the modular filters was compared with the performance of positional non-recursive filters implemented on a digital signal processor. An example of the estimation of the hardware costs is shown to be required for implementing a modular digital filter with a modified structure. This paper substantiates the expediency of applying the natural redundancy of finite field algebra codes on the example of the possibility to reduce hardware costs by a factor of two. It is demonstrated that the accuracy of data processing in the modular digital filter is higher than the accuracy achieved with the implementation of filters on digital processors. The accuracy advantage of the proposed approach is shown experimentally by the construction of the frequency response of the non-recursive low-pass filters.

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Wang, Gang, Hexin Chen, Mianshu Chen, Qiang Zhao, and Yingjie Song. "Fractional-pel Interpolation Algorithm Based on Adaptive Filter." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 08 (November 18, 2019): 2054022. http://dx.doi.org/10.1142/s0218001420540221.

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In order to further improve fractional-pel interpolation image quality of video sequence with different resolutions and reduce algorithm complexity, the fractional-pel interpolation algorithm based on adaptive filter (AF_FIA) is proposed. This algorithm adaptively selects the interpolation filters with different orders according to the three video sequence regions with different resolutions; in the three video sequence regions with different resolutions, the high-order interpolation filter is replaced by low-order interpolation filter according to the correlation between pixels to realize the adaptive selection of filter. The complexity analysis results show that compared with other algorithms, this algorithm reduces space complexity and computation complexity, thus reducing the storage access and coding time. The simulation results indicate that compared with other algorithms, this algorithm has good coding performance and robustness for video sequences with different resolutions.

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Parlos, Alexander G., Sunil K. Menon, and Amir F. Atiya. "An Adaptive State Filtering Algorithm for Systems With Partially Known Dynamics." Journal of Dynamic Systems, Measurement, and Control 124, no. 3 (July 23, 2002): 364–74. http://dx.doi.org/10.1115/1.1485747.

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On-line filtering of stochastic variables that are difficult or expensive to directly measure has been widely studied. In this paper a practical algorithm is presented for adaptive state filtering when the underlying nonlinear state equations are partially known. The unknown dynamics are constructively approximated using neural networks. The proposed algorithm is based on the two-step prediction-update approach of the Kalman Filter. The algorithm accounts for the unmodeled nonlinear dynamics and makes no assumptions regarding the system noise statistics. The proposed filter is implemented using static and dynamic feedforward neural networks. Both off-line and on-line learning algorithms are presented for training the filter networks. Two case studies are considered and comparisons with Extended Kalman Filters (EKFs) performed. For one of the case studies, the EKF converges but it results in higher state estimation errors than the equivalent neural filter with on-line learning. For another, more complex case study, the developed EKF does not converge. For both case studies, the off-line trained neural state filters converge quite rapidly and exhibit acceptable performance. On-line training further enhances filter performance, decoupling the eventual filter accuracy from the accuracy of the assumed system model.

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Zhang, Jianming, Yang Liu, Hehua Liu, and Jin Wang. "Learning Local–Global Multiple Correlation Filters for Robust Visual Tracking with Kalman Filter Redetection." Sensors 21, no. 4 (February 5, 2021): 1129. http://dx.doi.org/10.3390/s21041129.

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Visual object tracking is a significant technology for camera-based sensor networks applications. Multilayer convolutional features comprehensively used in correlation filter (CF)-based tracking algorithms have achieved excellent performance. However, there are tracking failures in some challenging situations because ordinary features are not able to well represent the object appearance variations and the correlation filters are updated irrationally. In this paper, we propose a local–global multiple correlation filters (LGCF) tracking algorithm for edge computing systems capturing moving targets, such as vehicles and pedestrians. First, we construct a global correlation filter model with deep convolutional features, and choose horizontal or vertical division according to the aspect ratio to build two local filters with hand-crafted features. Then, we propose a local–global collaborative strategy to exchange information between local and global correlation filters. This strategy can avoid the wrong learning of the object appearance model. Finally, we propose a time-space peak to sidelobe ratio (TSPSR) to evaluate the stability of the current CF. When the estimated results of the current CF are not reliable, the Kalman filter redetection (KFR) model would be enabled to recapture the object. The experimental results show that our presented algorithm achieves better performances on OTB-2013 and OTB-2015 compared with the other latest 12 tracking algorithms. Moreover, our algorithm handles various challenges in object tracking well.

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Lamien, Bernard, Leonardo A. B. Varon, Helcio R. B. Orlande, and Guillermo E. Elicabe. "State estimation in bioheat transfer: a comparison of particle filter algorithms." International Journal of Numerical Methods for Heat & Fluid Flow 27, no. 3 (March 6, 2017): 615–38. http://dx.doi.org/10.1108/hff-03-2016-0118.

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Purpose The purpose of this paper is to focus on applications related to the hyperthermia treatment of cancer, with heating imposed either by a laser in the near-infrared range or by radiofrequency waves. The particle filter algorithms are compared in terms of computational time and solution accuracy. Design/methodology/approach The authors extend the analyses performed in their previous works to compare three different algorithms of the particle filter, as applied to the hyperthermia treatment of cancer. The particle filters examined here are the sampling importance resampling (SIR) algorithm, the auxiliary sampling importance resampling (ASIR) algorithm and Liu & West’s algorithm. Findings Liu & West’s algorithm resulted in the largest computational times. On the other hand, this filter was shown to be capable of dealing with very large uncertainties. In fact, besides the uncertainties in the model parameters, Gaussian noises, similar to those used for the SIR and ASIR filters, were added to the evolution models for the application of Liu & West’s filter. For the three filters, the estimated temperatures were in excellent agreement with the exact ones. Practical implications This work may help medical doctors in the future to prescribe treatment protocols and also opens the possibility of devising control strategies for the hyperthermia treatment of cancer. Originality/value The natural solution to couple the uncertain results from numerical simulations with the measurements that contain uncertainties, aiming at the better prediction of the temperature field of the tissues inside the body, is to formulate the problem in terms of state estimation, as performed in this work.

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Journal articles on the topic 'Filter Algorithmus'

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