Relevant bibliographies by topics / Performance of system identification techniques

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  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Performance of system identification techniques'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Performance of system identification techniques"

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Plummer, A. R., and N. D. Vaughan. "Discrete-Time System Identification for Electrohydraulic Servo Systems." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 209, no. 3 (August 1995): 165–77. http://dx.doi.org/10.1243/pime_proc_1995_209_381_02.

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The application of system identification to an electrohydraulic servo system is described. Identified models are used to design pole-placement controllers for the system. A variety of parameter estimators and model structure selection techniques are compared by assessing the performance of the controllers designed from the estimated models. The least squares method processing filtered data is found to yield reliable models, and an appropriate model structure can be selected successfully by comparing prediction errors for models of different structure.
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Zhang, E., R. Pintelon, and P. Guillaume. "Modal Identification Using OMA Techniques: Nonlinearity Effect." Shock and Vibration 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/178696.

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This paper is focused on an assessment of the state of the art of operational modal analysis (OMA) methodologies in estimating modal parameters from output responses of nonlinear structures. By means of the Volterra series, the nonlinear structure excited by random excitation is modeled as best linear approximation plus a term representing nonlinear distortions. As the nonlinear distortions are of stochastic nature and thus indistinguishable from the measurement noise, a protocol based on the use of the random phase multisine is proposed to reveal the accuracy and robustness of the linear OMA technique in the presence of the system nonlinearity. Several frequency- and time-domain based OMA techniques are examined for the modal identification of simulated and real nonlinear mechanical systems. Theoretical analyses are also provided to understand how the system nonlinearity degrades the performance of the OMA algorithms.
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Lin, Liu Hsu, Jai Yush Yen, and Fu Cheng Wang. "System Identification and Robust Control of a Pneumatic Muscle Actuator System." Applied Mechanics and Materials 284-287 (January 2013): 1936–40. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.1936.

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This paper describes the application of system identification techniques and robust control strategies to a pneumatic muscle actuator system. Due to the inherent nonlinear and time-varying characteristics of this system, it is difficult to achieve excellent performance using conventional control methods. Therefore, we apply identification techniques to model the system as linear transfer functions and regard the un-modeled dynamics as system uncertainties. Because robust control is well-known for its capability in dealing with system uncertainties, we then apply robust control strategies to guarantee system stability and performance for the system. This work is carried out in three parts. First, the pneumatic muscle actuator system was modeled as linear transfer functions. Second, robust control theorem were utilized to design a Hinf robust controller to deal with system uncertainties and performance requirements. Finally, the designed controller was implemented for experimental verifications and compared with a conventional PID controller. From the experimental results, the proposed Hinf robust controller is deemed effective.
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Papadopoulos, Panagiotis N., Grigoris K. Papagiannis, Andrew J. Roscoe, Paul Crolla, Theofilos A. Papadopoulos, and Graeme M. Burt. "Measurement-based analysis of the dynamic performance of microgrids using system identification techniques." IET Generation, Transmission & Distribution 9, no. 1 (January 8, 2015): 90–103. http://dx.doi.org/10.1049/iet-gtd.2014.0555.

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Jayanna, H. S., and B. G. Nagaraja. "An Experimental Comparison of Modeling Techniques and Combination of Speaker – Specific Information from Different Languages for Multilingual Speaker Identification." Journal of Intelligent Systems 25, no. 4 (October 1, 2016): 529–38. http://dx.doi.org/10.1515/jisys-2014-0128.

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AbstractMost of the state-of-the-art speaker identification systems work on a monolingual (preferably English) scenario. Therefore, English-language autocratic countries can use the system efficiently for speaker recognition. However, there are many countries, including India, that are multilingual in nature. People in such countries have habituated to speak multiple languages. The existing speaker identification system may yield poor performance if a speaker’s train and test data are in different languages. Thus, developing a robust multilingual speaker identification system is an issue in many countries. In this work, an experimental evaluation of the modeling techniques, including self-organizing map (SOM), learning vector quantization (LVQ), and Gaussian mixture model-universal background model (GMM-UBM) classifiers for multilingual speaker identification, is presented. The monolingual and crosslingual speaker identification studies are conducted using 50 speakers of our own database. It is observed from the experimental results that the GMM-UBM classifier gives better identification performance than the SOM and LVQ classifiers. Furthermore, we propose a combination of speaker-specific information from different languages for crosslingual speaker identification, and it is observed that the combination feature gives better performance in all the crosslingual speaker identification experiments.
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McKelvey, Tomas, Andrew Fleming, and S. O. Reza Moheimani. "Subspace-Based System Identification for an Acoustic Enclosure." Journal of Vibration and Acoustics 124, no. 3 (June 12, 2002): 414–19. http://dx.doi.org/10.1115/1.1467653.

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This paper is aimed at identifying a dynamical model for an acoustic enclosure, a duct with rectangular cross section, closed ends, and side-mounted speaker enclosures. Acoustic enclosures are known to be resonant systems of high order. In order to design a high performance feedback controller for an acoustic enclosure, one needs to have an accurate model of the system. Subspace-based system identification techniques have proven to be an efficient means of identifying dynamics of high order highly resonant systems. In this paper a frequency domain subspace-based method together with a second iterative optimization step minimizing a frequency domain least-squares criterion is successfully employed to identify a dynamical model for an acoustic enclosure.
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Hamd, Muthana Hachim. "Optimized biometric system based iris-signature for human identification." International Journal of Advances in Intelligent Informatics 5, no. 3 (October 29, 2019): 273. http://dx.doi.org/10.26555/ijain.v5i3.407.

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This research aimed at comparing iris-signature techniques, namely the Sequential Technique (ST) and the Standard Deviation Technique (SDT). Both techniques were measured by Backpropagation (BP), Probabilistic, Radial basis function (RBF), and Euclidian distance (ED) classifiers. A biometric system-based iris is developed to identify 30 of CASIA-v1 and 10 subjects from the Real-iris datasets. Then, the proposed unimodal system uses Fourier descriptors to extract the iris features and represent them as an iris-signature graph. The 150 values of input machine vector were optimized to include only high-frequency coefficients of the iris-signature, then the two optimization techniques are applied and compared. The first optimization (ST) selects sequentially new feature values with different lengths from the enrichment graph region that has rapid frequency changes. The second technique (SDT) chooses the high variance coefficients as a new feature of vectors based on the standard deviation formula. The results show that SDT achieved better recognition performance with the lowest vector-lengths, while Probabilistic and BP have the best accuracy.
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Fateh, Rachid, Anouar Darif, and Said Safi. "Performance Evaluation of MC-CDMA Systems with Single User Detection Technique using Kernel and Linear Adaptive Method." Journal of Telecommunictions and Information Technology 4, no. 2021 (December 30, 2021): 1–11. http://dx.doi.org/10.26636/jtit.2021.151621.

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Among all the techniques combining multi-carrier modulation and spread spectrum, the multi-carrier code division multiple access (MC-CDMA) system is by far the most widely studied. In this paper, we present the performance of the MC-CDMA system associated with key single-user detection techniques. We are interested in problems related to identification and equalization of mobile radio channels, using the kernel method in Hilbert space with a reproducing kernel, and a linear adaptive algorithm, for MC-CDMA systems. In this context, we tested the efficiency of these algorithms, considering practical frequency selective fading channels, called broadband radio access network (BRAN), standardized for MC-CDMA systems. As far as the equalization problem encountered after channel identification is concerned, we use the orthogonality restoration combination (ORC) and the minimum mean square error (MMSE) equalizer techniques to correct the distortion of the channel. Simulation results demonstrate that the kernel algorithm is efficient for practical channels.
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Gonzales, Oscar. "Parametric and Non-parametric Mathematical Modelling Techniques: A Practical Approach of an Electrical Machine Identification." Ecuadorian Science Journal 5, no. 1 (March 31, 2021): 30–36. http://dx.doi.org/10.46480/esj.5.1.86.

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Mathematical modeling is an important feature concerning the analysis and control of dynamic systems. Also, system identification is an approach for building mathematical expressions from experimental data taken from processes performance. In this context, the contemporaneous state of the art describes several modelling and identification techniques which are excellent alternatives to determine systems behavior through time. This paper presents a comprehensive review of the main techniques for modeling and identification from a parametric and no parametric perspective. Experimental data are taken from an electrical machine that is a DC motor from a didactic platform. The paper concludes with the analysis of results taken from different identification procedures.
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Rituerto-González, Esther, Alba Mínguez-Sánchez, Ascensión Gallardo-Antolín, and Carmen Peláez-Moreno. "Data Augmentation for Speaker Identification under Stress Conditions to Combat Gender-Based Violence." Applied Sciences 9, no. 11 (June 4, 2019): 2298. http://dx.doi.org/10.3390/app9112298.

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A Speaker Identification system for a personalized wearable device to combat gender-based violence is presented in this paper. Speaker recognition systems exhibit a decrease in performance when the user is under emotional or stress conditions, thus the objective of this paper is to measure the effects of stress in speech to ultimately try to mitigate their consequences on a speaker identification task, by using data augmentation techniques specifically tailored for this purpose given the lack of data resources for this condition. An extensive experimentation has been carried out for assessing the effectiveness of the proposed techniques. First, we conclude that the best performance is always obtained when naturally stressed samples are included in the training set, and second, when these are not available, their substitution and augmentation with synthetically generated stress-like samples improves the performance of the system.
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Dissertations / Theses on the topic "Performance of system identification techniques"

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Islami, Kleidi. "System identification and structural health monitoring of bridge structures." Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3423079.

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This research study addresses two issues for the identification of structural characteristics of civil infrastructure systems. The first one is related to the problem of dynamic system identification, by means of experimental and operational modal analysis, applied to a large variety of bridge structures. Based on time and frequency domain techniques and mainly with output-only acceleration, velocity or strain data, modal parameters have been estimated for suspension bridges, masonry arch bridges, concrete arch and continuous bridges, reticular and box girder steel bridges. After giving an in-depth overview of standard and advanced stochastic methods, differences of the existing approaches in their performances are highlighted during system identification on the different kinds of civil infrastructures. The evaluation of their performance is accompanied by easy and hard determinable cases, which gave good results only after performing advanced clustering analysis. Eventually, real-time vibration-based structural health monitoring algorithms are presented during their performance in structural damage detection by statistical models. The second issue is the noise-free estimation of high order displacements taking place on suspension bridges. Once provided a comprehensive treatment of displacement and acceleration data fusion for dynamic systems by defining the Kalman filter algorithm, the combination of these two kinds of measurements is achieved, improving the deformations observed. Thus, an exhaustive analysis of smoothed displacement data on a suspension bridge is presented. The successful tests were subsequently used to define the non-collocated sensor monitoring problem with the application on simplified models
Questo lavoro di ricerca mira a due obiettivi per l'identificazione delle caratteristiche strutturali dei sistemi infrastrutturali civili. Il primo è legato al problema della identificazione del sistema dinamico, mediante analisi modale sperimentale e operativa, applicata ad una grande varietà di strutture da ponte. Basandosi su tecniche nel dominio del tempo e delle frequenze e, soprattutto, su dati di output di accelerazione, velocità o strain, i parametri modali sono stati stimati per ponti sospesi, ponti ad arco in muratura, ponti a travi in calcestruzzo e ad arco, ponti reticolari e ponti in acciaio a cassone. Dopo aver dato una panoramica approfondita dei metodi stocastici standard ed avanzati, sono state evidenziate le differenze degli approcci esistenti nelle loro performance per l'identificazione del sistema sui diversi tipi di infrastrutture civili. La valutazione della loro performance viene accompagnata da casi facilmente e difficilmente determinabili, che hanno dato buoni risultati solo dopo l'esecuzione di analisi avanzate di Clustering. Inoltre, sono stati sviluppati algoritmi di identificazione dinamica automatica in tempo reale basandosi sulle vibrazioni strutturali dei ponti monitorati, a sua volta utilizzati nel rilevamento dei danni strutturali tramite modelli statistici. Il secondo problema studiato riguarda la stima di spostamenti di ordine superiore che si svolgono sui ponti sospesi, eliminando il rumore di misura e di processo. Una volta fornito un trattamento completo della fusione dei dati di spostamento e accelerazione per i sistemi dinamici tramite il filtro di Kalman, la combinazione di questi due tipi di misurazioni ha mostrato un miglioramento nelle deformazioni osservate. Pertanto, è stata presentata un'analisi esauriente di un ponte sospeso e dei sui dati dinamici e di spostamento filtrati. I test positivi sono stati successivamente utilizzati per definire il problema dei sensori non collocati alla stessa locazione ed applicazione su modelli semplificati
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Azevedo, João Henrique Albino de. "Aeroelastic studies using system identification techniques." Instituto Tecnológico de Aeronáutica, 2013. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=2864.

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The present work is concerned with studying techniques which would allow the identification of a multiple degree of freedom aeroelastic system from a single computational fluid dynamics (CFD) unsteady simulation. This data is, then, used to generate the root locus for aeroelastic stability analysis of the dynamic system. The system being considered in the present work is a NACA 0012 airfoil-based typical section in the transonic regime. The CFD calculations are based on the Euler equations and the code uses a finite volume formulation for general unstructured grids. A centered spatial discretization with added artificial dissipation is used, and an explicit Runge-Kutta time marching method is employed. Unsteady calculations are performed for several types of excitation on the plunge and pitch degrees of freedom of the dynamic system. These inputs are mostly based on step and orthogonal Walsh functions. System identification techniques are used to allow the splitting of the aerodynamic coeficient time histories into the contributions of each individual mode to the corresponding aerodynamic transfer functions. Such transfer functions are, then, represented by rational polynomials and used in an aeroelastic stability analysis in the frequency domain. The work compares the results provided for each case and attempts to contribute with guidelines for such analyses.
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Gorti, Bhaskar M. "Techniques for discrete, time domain system identification." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-11242009-020121/.

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Chen, Yi S. M. Massachusetts Institute of Technology. "Nonlinear stochastic system identification techniques for biological tissues/." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62122.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 205-212).
This research develops a device capable of measuring the nonlinear dynamic mechanical properties of human tissue in vivo. The enabling technology is the use of nonlinear stochastic system identification techniques in conjunction with a high bandwidth actuator to perturb the tissue. The desktop and handheld instruments used for this investigation were custom-built Lorentz force actuators which were able to measure the dynamic compliance between the input force and the output displacement. The actuators have a nominal stroke of 32 mm and were actuated with forces under 15 N. The design includes custom electronics and user software which collects and analyses the information. This research also explores nonlinear stochastic system identification techniques that would be applicable to biological tissues. Several system identification techniques were used including linear, Wiener static nonlinear, Volterra kernel and partitioning techniques. Real time system identification and real time input generation schemes are also implemented. The mathematical formulation and implementation details of these techniques are also discussed. It was found that a simple linear stochastic system identification technique had a variance accounted for (VAF) of 70 to 75 %. More complicated representations using Volterra kernels or partitioning techniques had a VAF of 90 to 97 %. More complex nonlinear system identification techniques can not only capture more of the nonlinear dynamics but also capture those dynamics in an interpretable way. Indentation, extension, and surface mechanics experiments were conducted to investigate the nonlinear mechanical compliance of skin in vivo. The techniques and devices used in this research can be applied directly to consumer product efficacy analysis, medical diagnosis as well as research in biomechanical tissues.
by Yi Chen.
S.M.
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Bihl, Trevor Joseph. "State Variable System Identification through Frequency Domain Techniques." Ohio University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1307128475.

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Shaw, Steven Robert 1973. "System identification techniques and modeling for nonintrusive load diagnostics." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/9119.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
Includes bibliographical references (p. 213-219).
This thesis addresses the requirements of a system that can detect on/off transients and identify physical parameters of loads connected to a power distribution network. The thesis emphasizes three areas; a transient classifier that recognizes load transients using a pattern matching scheme, parameter estimation techniques suited for use with this classifier, and case studies of modeling and identification motivated by diagnostics and performance monitoring. Together, these areas support applications that can extract detailed load information from centralized, easily accessible parts of a distribution network. A new approach and implementation of pattern-based nonintrusive transient classification is presented. The classifier is nonintrusive in the sense that it uses aggregated measurements at a central location and does not require instrumentation of individual loads. The classifier implementation includes a framework that integrates preprocessors for AC and DC environments, programs that present results, and load-specific parameter identification modules that are executed as their associated transients are classified. An obstacle for these parameter identification programs is that a good initial guess is needed for the iterative optimization routines typically used to find parameter estimates. Two approaches are given to overcome this problem for certain systems. The first extends conventional optimization methods to identify model parameters given a poor initial guess. The second approach treats the identification as a modeling problem and suggests ways to construct "inverse" models that map observations to parameter estimates without iteration. The techniques presented in the thesis are demonstrated with simulation data and in real world scenarios including a dormitory, an automobile, and an experimental building.
by Steven Robert Shaw.
Ph.D.
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Rocco, Claudio. "Techniques to analyse system performance under uncertainty." Thesis, Robert Gordon University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313442.

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Rajagopalan, Mohan. "Optimizing System Performance and Dependability Using Compiler Techniques." Diss., Tucson, Arizona : University of Arizona, 2006. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1439%5F1%5Fm.pdf&type=application/pdf.

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Topor, Zbigniew L. "Investigation of the human respiratory control system by computer modeling and system identification techniques." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0020/NQ47917.pdf.

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Emadi, Seyyedbehrad. "Application of observability techniques to structural system identification including shear effects." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/670565.

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According to Timoshenko’s beam theory, nodal rotations in beam-like structures are produced by bending and shear effects. On the one hand, bending rotations can be easily calculated by the Euler-Bernoulli stiffness matrix method. On the other hand, shear rotations are traditionally neglected as their effects are practically negligible in most structures. In addition, calculating the shear rotation effects by the stiffness matrix method is not straight forward tasks and it presents practical limitations. Nevertheless, this assumption might lead to significant errors in the simulation of the structural response of some structures (such as deep beams and composite structures). The shear effects are also neglected in the inverse analysis of structures (Structural System Identification) used to calibrate the mechanical properties of the structural elements from the monitoring on-site. Recently, one of the first methods for the inverse analysis of structures including the shear effects (the Observability Method, OM) was presented. This method introduced Timoshenko’s beam theory into the Stiffness Matrix Method (SMM). In this way, the vertical deflections produced by shear effects were included into the simulation while the shear rotations were neglected. In this method, the mechanical properties of the structures could be obtained from the nodal deflections measured on static tests on site. One of the main controversial features of this procedure is the fact that the measurement set must include rotations. This characteristic might be especially problematic in those structures where rotations due to shear are not negligible. In fact, in this case, neglecting the shear rotations might lead to significant errors. This simplification might be especially problematic in those structures where only rotations can be measured. In addition to the OM, some other inverse analysis methods including shear deformation effects have been recently presented in the literature. Nevertheless, all these methods also fail to deal with the shear rotation effects, as they only take into account in the system of equations the vertical deflections produced by shear. Therefore, when actual rotations on site are used estimations with significant errors can be obtained. To fill these gaps, this Ph.D. Thesis deals with the analysis of the effects of the shear deformations in beam-like structures from a direct and inverse approach. First of all, the SMM is updated to enable the calculation of the shear rotations from a direct analysis. This method is used to evaluate the effects of the shear rotations in beam-like structures with different slenderness ratios. In addition, for the first time in the literature, the slenderness ratios where the shear rotation effects can be neglected from a direct analysis are identified. Secondly, the OM is updated to enable the inverse analysis of structures with shear effects from measurement sets with only vertical deflections. This modification is based on the introduction of a numerical optimization method. With this aim, the inverse analysis of several examples of growing complexity are presented to illustrate the validity and potential of the updated method. Finally, the OM is modified to enable the inverse analysis from shear rotations. This modification is based on the introduction of a new iterative process to estimate successively the values of the shear rotations. To illustrate the applicability and potential of the proposed method, the inverse analysis of several examples of growing complexity is presented. A set of calculation recommendations and future researches are also proposed.
De acuerdo con la teoría de vigas de Timoshenko, las rotaciones nodales en estructuras tipo viga se producen por efectos de flexión y cortante. Si bien las rotaciones por flexión pueden ser fácilmente calculadas por el método de la matriz de rigidez de Euler-Bernoulli, las rotaciones por cortante no se han tomado en cuenta tradicionalmente ya que sus efectos son prácticamente insignificantes en la mayoría de las estructuras. Así mismo, el cálculo de los efectos de la rotación por cortante mediante el método de la matriz de rigidez no es una tarea sencilla y presenta limitaciones prácticas. Sin embargo, esta omisión podría conducir a errores significativos en la simulación de la respuesta estructural de algunas estructuras (como las vigas de gran canto). De igual forma, los efectos por cortante no han sido tomados en cuenta en el análisis inverso de las estructuras (Identificación del Sistema Estructural) que es utilizado para calibrar las propiedades mecánicas de los elementos estructurales a partir de la monitorización in situ. Recientemente, se presentó uno de los primeros métodos para el análisis inverso de las estructuras, incluidos los efectos por cortante (el método de observación, OM, por sus siglas en inglés). Este método introdujo la teoría de vigas de Timoshenko en el Método de la Matriz de Rigidez (SMM, por sus siglas en inglés). De esta manera, las flechas verticales producidas por los efectos por cortante se incluyeron en la simulación, mientras que las rotaciones por cortante se ignoraron. En este método, las propiedades mecánicas de las estructuras pudieron obtenerse a partir de las flechas nodales medidas en pruebas estáticas in situ. Una de las principales características controvertidas de este procedimiento es el hecho de que en el conjunto de mediciones se deben incluir las rotaciones. Esta característica podría ser especialmente problemática en aquellas estructuras en las que las rotaciones debidas al cortante no son despreciables. De hecho, en este caso, despreciar las rotaciones por cortante podría dar lugar a errores significativos. Además del OM, recientemente se han presentado en la literatura otros métodos de análisis inverso que incluyen los efectos de deformación por cortante. Sin embargo, tampoco ninguno de estos métodos aborda los efectos de rotación por cortante, ya que solo tienen en cuenta en el sistema de ecuaciones las deformaciones verticales producidas por cortante. Por lo tanto, cuando se utilizan las rotaciones reales in situ se pueden obtener estimaciones con errores significativos. Para llenar estos vacíos, esta Tesis Doctoral aborda el análisis de los efectos de las deformaciones por cortante en estructuras tipo viga desde un enfoque directo e inverso. En primer lugar, se actualiza el SMM para permitir el cálculo de las rotaciones por cortante a partir de un análisis directo. Este método se utiliza para evaluar los efectos de las rotaciones por cortante en estructuras tipo viga con diferentes ratios de esbeltez. Además, por primera vez en la literatura, se identifican los ratios de esbeltez en los que los efectos de la rotación por cortante pueden ser despreciados a partir de un análisis directo. En segundo lugar, el OM se ha actualizado para permitir el análisis inverso de estructuras con efectos de cortante a partir de un conjunto de mediciones con solo flechas verticales. Esta modificación se basa en la introducción de un método de optimización numérica. Con este objetivo, se presenta el análisis inverso de varios ejemplos de creciente complejidad para ilustrar la validez y el potencial del método actualizado. Por último, se modifica el OM para permitir el análisis inverso a partir de las rotaciones por cortante. Esta modificación se basa en la introducción de un nuevo proceso iterativo para estimar sucesivamente los valores de las rotaciones por cortante. Para ilustrar la aplicabilidad y el potencial del método propuesto, se presenta el análisis inverso de varios ejemplos de complejidad creciente. Así mismo, se propone un conjunto de recomendaciones de cálculo e investigaciones futuras.
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Books on the topic "Performance of system identification techniques"

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Hallenbeck, Mark E. Use of automatic vehicle identification techniques for measuring traffic performance and performing incident detection: Final report. [Olympia, Wash.?]: TransNow, Transportation Northwest, University Transportation Centers Program, Federal Region Ten, Washington State Dept. of Transportation, Transit, Research, and Intermodal Planning Division, in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1992.

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Bendat, Julius S. Nonlinear system techniques and applications. New York: Wiley, 1998.

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N, Kalouptsidis, and Theodoridis Sergios 1951-, eds. Adaptive system identification and signal processing algorithms. New York: Prentice Hall, 1993.

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Elsworth, John T. Design and performance of biometric system. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Song, Bang-Sup. System-level Techniques for Analog Performance Enhancement. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27921-3.

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Oracle9i performance tuning tips & techniques. New York: McGraw-Hill/Osborne, 2003.

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United States. National Aeronautics and Space Administration., ed. System identification and model reduction using modulating funciton techniques. Providence, R.I: Brown University, Division of Engineering, 1993.

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United States. National Aeronautics and Space Administration., ed. System identification and model reduction using modulating funciton techniques. Providence, R.I: Brown University, Division of Engineering, 1993.

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United States. Federal Highway Administration. Office of Highway Information Management., ed. Highway performance monitoring system catalog: New technology and techniques. [Washington, D.C.?]: Dept. of Transportation, Federal Highway Administration, Office of Highway Information Management, 1998.

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Peyrebrune, Henry L. Highway performance monitoring system catalog: New technology and techniques. [Washington, D.C.?]: Dept. of Transportation, Federal Highway Administration, Office of Highway Information Management, 1998.

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Book chapters on the topic "Performance of system identification techniques"

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San Mart ín, César, Pablo Meza, Sergio Torres, and Roberto Carrillo. "Improved Infrared Face Identification Performance Using Nonuniformity Correction Techniques." In Advanced Concepts for Intelligent Vision Systems, 1115–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88458-3_101.

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Hazra, Saumyadip, and Souvik Ganguli. "Comparative Performance Analysis of Multi-Objective Metaheuristic Approaches for Parameter Identification of Three-Diode-Modeled Photovoltaic Cells." In Introduction to AI Techniques for Renewable Energy Systems, 325–46. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003104445-20.

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Gebrealif, Yodit, Mohammed Mubarkoot, Jörn Altmann, and Bernhard Egger. "Architecture for Orchestrating Containers in Cloud Federations." In Economics of Grids, Clouds, Systems, and Services, 66–75. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92916-9_6.

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AbstractContainerization technology helps achieving not only better portability and interoperability but also better performance and efficiency on various cloud computing arrangements. Such technology is expected to empower cloud federations by enhancing portability and scalability across the federation. In this paper, we propose an architecture by adding two subcomponents to the NIST reference architecture for identifying resources and managing container orchestration in cloud federation environments. The architecture adds two subcomponents to the NIST reference architecture. The proposed two new sub-components enable resource identification and container orchestration across cloud federation members. These names of the two subcomponents are the Resource Identifier and the Container Orchestrator, respectively. The Resource Identifier component identifies the appropriate federated member for allocating tasks based on previous experience and current status. The Container Orchestrator facilitates the management and orchestration of containers at the federation level. We also identified several techniques, which can be used for resource identification. Among those, linear regression technique is selected for resource provisioning and identification of federation members. Further, these techniques are also expected to learn from log files from previous executions and prioritize resources based on the current resource status and previous experience.
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Singh, Ishwar, Krishan Kumar, Prabha Singh, Pranjal Yadava, and Sujay Rakshit. "Physiological and molecular interventions for improving nitrogen-use efficiency in maize." In Molecular breeding in wheat, maize and sorghum: strategies for improving abiotic stress tolerance and yield, 325–39. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245431.0019.

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Abstract This chapter discusses (i) the importance of nitrogen in plant growth and development, (ii) what is nitrogen-use efficiency (NUE) and how to manage it, (iii) traits influencing nitrogen-uptake efficiency including root system architecture, root nitrogen transporter system, and interaction with microorganisms, (iv) traits influencing nitrogen-utilization efficiency, such as nitrate assimilation, canopy photosynthesis per unit of nitrogen, (v) identification and use of quantitative trait loci (QTLs) related to NUE, (vi) identification of nitrogen-responsive genes, and (vii) nitrogen signalling and transduction for improving NUE. Intensive research on molecular and genetic aspects of NUE has led to the identification of many new genes, QTLs and alleles that could be deployed to develop new genotypes. The future direction of the research efforts should be towards understanding the interaction of NUE-related genes with cellular small RNA flux and perturbing the system performance through metabolic engineering and genome editing techniques.
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Chen, Ben M., Tong H. Lee, and Venkatakrishnan Venkataramanan. "System Identification Techniques." In Hard Disk Drive Servo Systems, 15–27. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-3712-2_2.

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Chinarro, David. "System Identification Techniques." In Springer Theses, 11–51. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08858-7_2.

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Nelles, Oliver. "Unsupervised Learning Techniques." In Nonlinear System Identification, 137–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04323-3_6.

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Nelles, Oliver. "Unsupervised Learning Techniques." In Nonlinear System Identification, 153–73. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47439-3_6.

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Mullen, Thomas J., S. M. Ramakrishna Mukkamala, and Richard J. Cohen. "Cardiovascular System Identification." In Advances in Noninvasive Electrocardiographic Monitoring Techniques, 453–61. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4090-4_44.

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Bohlin, Torsten. "Validation techniques." In Interactive System Identification: Prospects and Pitfalls, 220–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-48618-0_7.

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Conference papers on the topic "Performance of system identification techniques"

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Awathe, Arpit, Tejas Varunjikar, and Subhabrata Ganguli. "System Identification Techniques to Improve ADAS Feature Performance." In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2022. http://dx.doi.org/10.4271/2022-01-0091.

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Nusrath, Khadeeja, Jatinder Singh, and Basappa. "Drag assessment of a high performance aircraft using system identification techniques." In 2016 Indian Control Conference (ICC). IEEE, 2016. http://dx.doi.org/10.1109/indiancc.2016.7441168.

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Shahbaz, Muhammad, Sajida Parveen, Aziz Guergachi, and Karim Keshavjee. "Performance Analysis of Clinical Abbreviation Disambiguation Using Machine Learning Techniques." In Modelling, Simulation and Identification / 854: Intelligent Systems and Control. Calgary,AB,Canada: ACTAPRESS, 2017. http://dx.doi.org/10.2316/p.2017.854-003.

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Lew, Jiann-Shiun. "Structural Damage Identification With Performance-Based Uncertainty Quantification." In ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2010. http://dx.doi.org/10.1115/smasis2010-3622.

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This paper presents an investigation of damage detection of a structure with significant uncertainty. The proposed approach integrates the performance-based uncertainty quantification and feedback control techniques for damage identification. A singular value decomposition (SVD) technique is used to decompose parameter variations into principal components that are weighted with the sensitivity of the performance metric for damage detection. This SVD technique can be used to differentiate between dominant uncertainties and minor uncertainties corresponding to damage identification. To improve the performance of damage identification under uncertainty, a feedback controller is incorporated into the structure to reduce the effect of the quantified uncertainty. The probability framework, based on Monte Carlo simulation, is used to predict the false identification of damage. Examples based on the structural dynamics challenge problem issued by Sandia National Laboratories are used to demonstrate the proposed techniques.
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Vunnava, Reshma, Lakshmikanth Bodla, Mohan Kumar Dehury, and Bhabendu Kumar Mohanta. "Performance Analysis of ML Techniques in Identification of Fake News." In 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). IEEE, 2022. http://dx.doi.org/10.1109/icscds53736.2022.9760905.

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del Toro, Rau´l M., Michael C. Schmittdiel, Rodolfo E. Haber-Guerra, and Rodolfo Haber-Haber. "System Identification of the High Performance Drilling Process for Network-Based Control." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-34307.

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A simple, fast, network-based experimental procedure for identifying the dynamics of the high-performance drilling (HPD) process is proposed and successfully applied. This identification technique utilizes a single-input (feed rate), single-output (resultant force) system with a dual step input function. The model contains the delays of both the network architecture (a PROFIBUS type network) and the dead time related with the plant dynamic itself. Classical identification techniques are used to obtain first order, second order, and third order models on the basis of the recorded input/output data. The developed models relate the dynamic behavior of resultant force versus commanded feed rate in HPD. Model validation is performed through error-based performance indices and correlation analyses. Experimental verification is performed using two different work piece materials. The models match perfectly with real-time force behavior in drilling operations and are easily integrated with many control strategies. Furthermore, these results demonstrate that the HPD process is somewhat non-linear with a remarkable difference in gain due to work piece material; however, the dynamic behavior does not change significantly.
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Swayamsiddha, Swati, Sabyasachi Behera, and H. Pal Thethi. "Blind Identification of Nonlinear MIMO System Using Differential Evolution Techniques and Performance Analysis of Its Variants." In 2015 International Conference on Computational Intelligence & Networks (CINE). IEEE, 2015. http://dx.doi.org/10.1109/cine.2015.22.

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Thanh, Le Trung, Karim Abed-Meraim, and Nguyen Linh Trung. "Performance Lower Bounds of Blind System Identification Techniques in the Presence of Channel Order Estimation Error." In 2021 29th European Signal Processing Conference (EUSIPCO). IEEE, 2021. http://dx.doi.org/10.23919/eusipco54536.2021.9615921.

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Durou, Amal, Ibrahim Aref, Mosa Elbendak, Sumaya Al-Maadeed, and Ahmed Bouridane. "Measuring and optimising performance of an offline text writer identification system in terms of dimensionality reduction techniques." In 2017 Seventh International Conference on Emerging Security Technologies (EST). IEEE, 2017. http://dx.doi.org/10.1109/est.2017.8090393.

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Bird, Jeff W., and Howard M. Schwartz. "Diagnosis of Turbine Engine Transient Performance With Model-Based Parameter Estimation Techniques." In ASME 1994 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/94-gt-317.

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This review surveys knowledge needed to develop an improved method of modelling the dynamics of gas turbine performance for fault diagnosis applications. Aerothermodynamic and control models of gas turbine processes are examined as complementary to models derived directly from test data. Extensive, often proprietary data are required for physical models of components, while system identification (SI) methods need data from specially-designed tests. Current methods are limited in: tuning models to test data, non-linear effects, component descriptions in SI models, robustness to noise, and inclusion of control systems and actuators. Conclusions are drawn that SI models could be formulated, with parameters which describe explicitly the functions of key engine components, to offer improved diagnostic capabilities.
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Reports on the topic "Performance of system identification techniques"

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Kalman, Rudolf E. Mathematical Techniques for System Realization and Identification. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada207927.

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Kalman, R. E. Mathematical Techniques for System Realization and Identification. Fort Belvoir, VA: Defense Technical Information Center, June 1989. http://dx.doi.org/10.21236/ada212088.

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Kalman, R. E. Mathematical Techniques for System Realization and Identification. Fort Belvoir, VA: Defense Technical Information Center, February 1986. http://dx.doi.org/10.21236/ada174487.

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Klyde, David, Chuck Harris, Peter M. Thompson, and Edward N. Bachelder. System Identification Methods for Improving Flutter Flight Test Techniques. Fort Belvoir, VA: Defense Technical Information Center, August 2004. http://dx.doi.org/10.21236/ada426452.

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Steele, L. L., J. R. Grant, Harrold Jr., Erhart D. P., Anex J. J., and R. P. Application of System Identification Techniques to Combustor Poststall Dynamics. Fort Belvoir, VA: Defense Technical Information Center, September 1987. http://dx.doi.org/10.21236/ada187898.

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Pierre, John W., Richard Wies, and Daniel Trudnowski. Advanced Techniques for Power System Identification from Measured Data. Office of Scientific and Technical Information (OSTI), November 2008. http://dx.doi.org/10.2172/943294.

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Popken, Douglas A., and Louis A. Cox. An Investigation of System Identification Techniques for Simulation Model Abstraction. Fort Belvoir, VA: Defense Technical Information Center, February 2000. http://dx.doi.org/10.21236/ada375285.

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Bialasiewicz, Jan T. Advanced System Identification Techniques for Wind Turbine Structures with Special Emphasis on Modal Parameters. Office of Scientific and Technical Information (OSTI), June 1995. http://dx.doi.org/10.2172/87043.

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Anex, Robert P. Application of System Identification Techniques to Turbine Engine Post-Stall Test and Evaluation. Volume 1. Fort Belvoir, VA: Defense Technical Information Center, December 1990. http://dx.doi.org/10.21236/ada239181.

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P. D. Mattie, J. A. McNeish, D. S. Sevougian, and R. W. Andrews. Methods and Techniques Used to Convey Total System Performance Assessment Analyses and Results for Site Recommendation at Yucca Mountain, Nevada, USA. Office of Scientific and Technical Information (OSTI), April 2001. http://dx.doi.org/10.2172/786563.

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