Efficient Nonlinear Adaptive Filters
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Efficient Nonlinear Adaptive Filters
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Author : Haiquan Zhao
language : en
Publisher: Springer Nature
Release Date : 2023-02-10
Efficient Nonlinear Adaptive Filters written by Haiquan Zhao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-10 with Technology & Engineering categories.
This book presents the design, analysis, and application of nonlinear adaptive filters with the goal of improving efficient performance (ie the convergence speed, steady-state error, and computational complexity). The authors present a nonlinear adaptive filter, which is an important part of nonlinear system and digital signal processing and can be applied to diverse fields such as communications, control power system, radar sonar, etc. The authors also present an efficient nonlinear filter model and robust adaptive filtering algorithm based on the local cost function of optimal criterion to overcome non-Gaussian noise interference. The authors show how these achievements provide new theories and methods for robust adaptive filtering of nonlinear and non-Gaussian systems. The book is written for the scientist and engineer who are not necessarily an expert in the specific nonlinear filtering field but who want to learn about the current research and application. The book is also written to accompany a graduate/PhD course in the area of nonlinear system and adaptive signal processing.
Adaptive Learning Methods For Nonlinear System Modeling
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Author : Danilo Comminiello
language : en
Publisher: Butterworth-Heinemann
Release Date : 2018-07-05
Adaptive Learning Methods For Nonlinear System Modeling written by Danilo Comminiello and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-05 with Technology & Engineering categories.
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.
Nonlinear Digital Filters
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Author : Ioannis Pitas
language : en
Publisher: Springer Science & Business Media
Release Date : 1990-01-31
Nonlinear Digital Filters written by Ioannis Pitas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-01-31 with Technology & Engineering categories.
To date, no unifying theory has been developed which encompasses nonlinear filters in the same theoretical framework. This book takes strides in that direction by organizing nonlinear filter classes in a concise way and stretching their common properties. Annotation copyrighted by Book News, Inc., Portland, OR
Adaptive Filters
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Author : Ali H. Sayed
language : en
Publisher: Wiley-IEEE Press
Release Date : 2008-04-14
Adaptive Filters written by Ali H. Sayed and has been published by Wiley-IEEE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-14 with Science categories.
"Adaptive Filters allows readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. - This book will interest students, experts, practitioners and instructors."--BOOK JACKET.
Principles Of Adaptive Filters And Self Learning Systems
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Author : Anthony Zaknich
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-04-25
Principles Of Adaptive Filters And Self Learning Systems written by Anthony Zaknich and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-25 with Technology & Engineering categories.
Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems
Complex Valued Nonlinear Adaptive Filters
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Author : Danilo P. Mandic
language : en
Publisher: John Wiley & Sons
Release Date : 2009-04-20
Complex Valued Nonlinear Adaptive Filters written by Danilo P. Mandic and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-20 with Science categories.
This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback architectures and the recent developments in the statistics of complex variable, under the powerful frameworks of CR (Wirtinger) calculus and augmented complex statistics. This offers a number of theoretical performance gains, which is illustrated on both stochastic gradient algorithms, such as the augmented complex least mean square (ACLMS), and those based on Kalman filters. This work is supported by a number of simulations using synthetic and real world data, including the noncircular and intermittent radar and wind signals.
Least Mean Square Adaptive Filters
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Author : Simon Haykin
language : en
Publisher: John Wiley & Sons
Release Date : 2003-09-08
Least Mean Square Adaptive Filters written by Simon Haykin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-08 with Technology & Engineering categories.
Edited by the original inventor of the technology. Includes contributions by the foremost experts in the field. The only book to cover these topics together.
Nonlinear Control And Filtering Using Differential Flatness Approaches
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Author : Gerasimos G. Rigatos
language : en
Publisher: Springer
Release Date : 2015-06-05
Nonlinear Control And Filtering Using Differential Flatness Approaches written by Gerasimos G. Rigatos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-05 with Technology & Engineering categories.
This monograph presents recent advances in differential flatness theory and analyzes its use for nonlinear control and estimation. It shows how differential flatness theory can provide solutions to complicated control problems, such as those appearing in highly nonlinear multivariable systems and distributed-parameter systems. Furthermore, it shows that differential flatness theory makes it possible to perform filtering and state estimation for a wide class of nonlinear dynamical systems and provides several descriptive test cases. The book focuses on the design of nonlinear adaptive controllers and nonlinear filters, using exact linearization based on differential flatness theory. The adaptive controllers obtained can be applied to a wide class of nonlinear systems with unknown dynamics, and assure reliable functioning of the control loop under uncertainty and varying operating conditions. The filters obtained outperform other nonlinear filters in terms of accuracy of estimation and computation speed. The book presents a series of application examples to confirm the efficiency of the proposed nonlinear filtering and adaptive control schemes for various electromechanical systems. These include: · industrial robots; · mobile robots and autonomous vehicles; · electric power generation; · electric motors and actuators; · power electronics; · internal combustion engines; · distributed-parameter systems; and · communication systems. Differential Flatness Approaches to Nonlinear Control and Filtering will be a useful reference for academic researchers studying advanced problems in nonlinear control and nonlinear dynamics, and for engineers working on control applications in electromechanical systems.
Kernel Adaptive Filtering
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Author : Weifeng Liu
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Kernel Adaptive Filtering written by Weifeng Liu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Science categories.
Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters. Covers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm Presents a powerful model-selection method called maximum marginal likelihood Addresses the principal bottleneck of kernel adaptive filters—their growing structure Features twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site Concludes each chapter with a summary of the state of the art and potential future directions for original research Kernel Adaptive Filtering is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.
Concept Of Adaptive Filtering
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Author : Shivendra Nandan
language : en
Publisher: TSG Publications
Release Date :
Concept Of Adaptive Filtering written by Shivendra Nandan and has been published by TSG Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.
A spline adaptive filter (SAF) based nonlinear active noise control (ANC) system is proposed in this paper. The SAF consists of a linear network of adaptive weights in a cascade with an adaptive nonlinear network. The nonlinear network, in turn consists of an adaptive look-up table followed by a spline interpolation network and forms an adaptive activation function. An update rule has been derived for the proposed ANC system, which not only updates the weights of the linear network, but also updates the nature of the activation function. Linear Network is based on improvement in FxLMS algorithm. FxLMS algorithm is used because it is computationally simple like the most commonly used Least Mean Square (LMS) algorithm. In addition, it includes secondary path effects. To make the FxLMS algorithm more effective, the secondary path estimation should be more precise and accurate. The nonlinear function involved in the adaptation process is based on a spline function that can be modified during learning. The spline control points are adaptively changed using gradient-based techniques. B-splines and Catmull-Rom splines are used, because they allow imposing simple constraints on control parameters. This new kind of adaptive function is then applied to the output of a linear adaptive filter and it is used for the identification of Wiener-type nonlinear systems. In addition, we derive a simple form of the adaptation algorithm and an upper bound on the choice of the step-size. An extensive simulation study has been conducted to evaluate the noise mitigation performance of the proposed scheme and the new method has been shown to provide improved noise cancellation efficiency with a lesser computational load in comparison with other popular ANC systems.