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Author : Bryan Scott Nollett
Release : 2002
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Efficient Nonlinear Adaptive Filtering Using the Wiener-Hammerstein System Model by : Bryan Scott Nollett
Download or read book Efficient Nonlinear Adaptive Filtering Using the Wiener-Hammerstein System Model written by Bryan Scott Nollett. This book was released on 2002. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Haiquan Zhao
Release : 2023-02-10
Genre : Technology & Engineering
Kind : eBook
Book Rating : 188/5 ( reviews)
Book Synopsis Efficient Nonlinear Adaptive Filters by : Haiquan Zhao
Download or read book Efficient Nonlinear Adaptive Filters written by Haiquan Zhao. This book was released on 2023-02-10. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Danilo P. Mandic
Release : 2009-04-20
Genre : Science
Kind : eBook
Book Rating : 631/5 ( reviews)
Book Synopsis Complex Valued Nonlinear Adaptive Filters by : Danilo P. Mandic
Download or read book Complex Valued Nonlinear Adaptive Filters written by Danilo P. Mandic. This book was released on 2009-04-20. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Danilo Comminiello
Release : 2018-06-11
Genre : Technology & Engineering
Kind : eBook
Book Rating : 778/5 ( reviews)
Book Synopsis Adaptive Learning Methods for Nonlinear System Modeling by : Danilo Comminiello
Download or read book Adaptive Learning Methods for Nonlinear System Modeling written by Danilo Comminiello. This book was released on 2018-06-11. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Shivendra Nandan
Release :
Genre : Education
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Concept of Adaptive Filtering by : Shivendra Nandan
Download or read book Concept of Adaptive Filtering written by Shivendra Nandan. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt: 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.
