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Book Convergence Study for Adaptive Allpass Filtering

Download or read book Convergence Study for Adaptive Allpass Filtering written by Paul Oprisan and published by . This book was released on 1998 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive filtering may be applied in areas where an optimal filtering algorithm may not be known a-priori and where the filtering operation may be non-stationary. This field, or more generally, the field of adaptive systems, is one which may be regarded as mature, having been the subject of considerable research effort in the areas of control and signal processing for almost four decades. DFE (decision feedback equalization) in various forms has been proposed for detection on magnetic recording channel. An allpass filter is an alternative to the FIR (finite impulse response) forward equalizer which is normally implemented with DFE. This is because the allpass filter is a lower power and complexity alternative, though its behavior and performance are not very well understood yet. Here, an allpass structure implemented as first and second order IIR (infinite impulse response) filters is examined. Convergence for the LMS (least mean square) adaptation algorithm is studied and, moreover, some convergence conditions and bounds are developed, similarly to the well known FIR case. This thesis provides an useful analytical study of convergence of IIR adaptive filtering. This is accomplished by a systematic approximation of the covariance terms of the adaptive coefficients. The range of the step-size parameter of the LMS algorithm is developed under some simplifying assumptions. All the results obtained are verified by simulation (Matlab and C routines are used).

Book Subband Adaptive Filtering

Download or read book Subband Adaptive Filtering written by Kong-Aik Lee and published by John Wiley & Sons. This book was released on 2009-07-06 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Subband adaptive filtering is rapidly becoming one of the most effective techniques for reducing computational complexity and improving the convergence rate of algorithms in adaptive signal processing applications. This book provides an introductory, yet extensive guide on the theory of various subband adaptive filtering techniques. For beginners, the authors discuss the basic principles that underlie the design and implementation of subband adaptive filters. For advanced readers, a comprehensive coverage of recent developments, such as multiband tap–weight adaptation, delayless architectures, and filter–bank design methods for reducing band–edge effects are included. Several analysis techniques and complexity evaluation are also introduced in this book to provide better understanding of subband adaptive filtering. This book bridges the gaps between the mixed–domain natures of subband adaptive filtering techniques and provides enough depth to the material augmented by many MATLAB® functions and examples. Key Features: Acts as a timely introduction for researchers, graduate students and engineers who want to design and deploy subband adaptive filters in their research and applications. Bridges the gaps between two distinct domains: adaptive filter theory and multirate signal processing. Uses a practical approach through MATLAB®-based source programs on the accompanying CD. Includes more than 100 M-files, allowing readers to modify the code for different algorithms and applications and to gain more insight into the theory and concepts of subband adaptive filters. Subband Adaptive Filtering is aimed primarily at practicing engineers, as well as senior undergraduate and graduate students. It will also be of interest to researchers, technical managers, and computer scientists.

Book Adaptive Filtering

Download or read book Adaptive Filtering written by Paulo S. R. Diniz and published by Springer Science & Business Media. This book was released on 2008-05-22 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner, using clear notations that facilitate actual implementation. Important algorithms are described in detailed tables which allow the reader to verify learned concepts. The book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, IIR adaptive filtering, and more. The book is also supported by a web page maintained by the author.

Book Adaptive Filters

Download or read book Adaptive Filters written by Behrouz Farhang-Boroujeny and published by John Wiley & Sons. This book was released on 2013-04-02 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of Adaptive Filters: Theory and Applications has been updated throughout to reflect the latest developments in this field; notably an increased coverage given to the practical applications of the theory to illustrate the much broader range of adaptive filters applications developed in recent years. The book offers an easy to understand approach to the theory and application of adaptive filters by clearly illustrating how the theory explained in the early chapters of the book is modified for the various applications discussed in detail in later chapters. This integrated approach makes the book a valuable resource for graduate students; and the inclusion of more advanced applications including antenna arrays and wireless communications makes it a suitable technical reference for engineers, practitioners and researchers. Key features: • Offers a thorough treatment of the theory of adaptive signal processing; incorporating new material on transform domain, frequency domain, subband adaptive filters, acoustic echo cancellation and active noise control. • Provides an in-depth study of applications which now includes extensive coverage of OFDM, MIMO and smart antennas. • Contains exercises and computer simulation problems at the end of each chapter. • Includes a new companion website hosting MATLAB® simulation programs which complement the theoretical analyses, enabling the reader to gain an in-depth understanding of the behaviours and properties of the various adaptive algorithms.

Book Fundamentals of Adaptive Filtering

Download or read book Fundamentals of Adaptive Filtering written by Ali H. Sayed and published by John Wiley & Sons. This book was released on 2003-06-13 with total page 1172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on a graduate level course offered by the author at UCLA and has been classed tested there and at other universities over a number of years. This will be the most comprehensive book on the market today providing instructors a wide choice in designing their courses. * Offers computer problems to illustrate real life applications for students and professionals alike * An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

Book Development and Analysis of an Adaptive Heterodyne Filter

Download or read book Development and Analysis of an Adaptive Heterodyne Filter written by Karl Einar Nelson and published by . This book was released on 2001 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book A Rapid Introduction to Adaptive Filtering

Download or read book A Rapid Introduction to Adaptive Filtering written by Leonardo Rey Vega and published by Springer Science & Business Media. This book was released on 2012-08-07 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative methods for solving the optimization problem, e.g., the Method of Steepest Descent. By proposing stochastic approximations, several basic adaptive algorithms are derived, including Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS) and Sign-error algorithms. The authors provide a general framework to study the stability and steady-state performance of these algorithms. The affine Projection Algorithm (APA) which provides faster convergence at the expense of computational complexity (although fast implementations can be used) is also presented. In addition, the Least Squares (LS) method and its recursive version (RLS), including fast implementations are discussed. The book closes with the discussion of several topics of interest in the adaptive filtering field.

Book Principles of Adaptive Filters and Self learning Systems

Download or read book Principles of Adaptive Filters and Self learning Systems written by Anthony Zaknich and published by Springer Science & Business Media. This book was released on 2005-04-25 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Adaptive Filters

    Book Details:
  • Author : Ali H. Sayed
  • Publisher : John Wiley & Sons
  • Release : 2011-10-11
  • ISBN : 1118210840
  • Pages : 1295 pages

Download or read book Adaptive Filters written by Ali H. Sayed and published by John Wiley & Sons. This book was released on 2011-10-11 with total page 1295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive filtering is a topic of immense practical and theoretical value, having applications in areas ranging from digital and wireless communications to biomedical systems. This book enables 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. The book consists of eleven parts?each part containing a series of focused lectures and ending with bibliographic comments, problems, and computer projects with MATLAB solutions.

Book Adaptive Filtering

    Book Details:
  • Author : Wenping Cao
  • Publisher : BoD – Books on Demand
  • Release : 2021-10-20
  • ISBN : 1839623772
  • Pages : 154 pages

Download or read book Adaptive Filtering written by Wenping Cao and published by BoD – Books on Demand. This book was released on 2021-10-20 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Active filters are key technologies in applications such as telecommunications, advanced control, smart grids, and green transport. This book provides an update of the latest technological progress in signal processing and adaptive filters, with a focus on Kalman filters and applications. It illustrates fundamentals and guides filter design for specific applications, primarily for graduate students, academics, and industrial engineers who are interested in the theoretical, experimental, and design aspects of active filter technologies.

Book Partial Update Least Square Adaptive Filtering

Download or read book Partial Update Least Square Adaptive Filtering written by Bei Xie and published by Springer Nature. This book was released on 2022-05-31 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity ($O(N)$) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster and have lower steady-state mean square error (MSE) than LMS. However, their high computational complexity ($O(N^2)$) makes them unsuitable for many real-time applications. A well-known approach to controlling computational complexity is applying partial update (PU) method to adaptive filters. A partial update method can reduce the adaptive algorithm complexity by updating part of the weight vector instead of the entire vector or by updating part of the time. In the literature, there are only a few analyses of these partial update adaptive filter algorithms. Most analyses are based on partial update LMS and its variants. Only a few papers have addressed partial update RLS and Affine Projection (AP). Therefore, analyses for PU least-squares adaptive filter algorithms are necessary and meaningful. This monograph mostly focuses on the analyses of the partial update least-squares adaptive filter algorithms. Basic partial update methods are applied to adaptive filter algorithms including Least Squares CMA (LSCMA), EDS, and CG. The PU methods are also applied to CMA1-2 and NCMA to compare with the performance of the LSCMA. Mathematical derivation and performance analysis are provided including convergence condition, steady-state mean and mean-square performance for a time-invariant system. The steady-state mean and mean-square performance are also presented for a time-varying system. Computational complexity is calculated for each adaptive filter algorithm. Numerical examples are shown to compare the computational complexity of the PU adaptive filters with the full-update filters. Computer simulation examples, including system identification and channel equalization, are used to demonstrate the mathematical analysis and show the performance of PU adaptive filter algorithms. They also show the convergence performance of PU adaptive filters. The performance is compared between the original adaptive filter algorithms and different partial-update methods. The performance is also compared among similar PU least-squares adaptive filter algorithms, such as PU RLS, PU CG, and PU EDS. In addition to the generic applications of system identification and channel equalization, two special applications of using partial update adaptive filters are also presented. One application uses PU adaptive filters to detect Global System for Mobile Communication (GSM) signals in a local GSM system using the Open Base Transceiver Station (OpenBTS) and Asterisk Private Branch Exchange (PBX). The other application uses PU adaptive filters to do image compression in a system combining hyperspectral image compression and classification.

Book Frequency Domain Maximum Likelihood Adaptive Filtering

Download or read book Frequency Domain Maximum Likelihood Adaptive Filtering written by Chung-Yen Ong and published by . This book was released on 1970 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent intensive study of adaptive (gradient-search) filtering in the time domain has not solved the problems with rate-of-convergence problem, which is a major difficulty with this technique. A recent study based on a set of time-stationary synthetic data shows that the time-domain maximum-likelihood adaptive filter converges very slowly to the optimum filter. After 3300 iterations of adaption with an adaptive rate of 10 percent of maximum value, the adaptive filter is still about 4 db away from the optimum filter in the sense of mean-square outputs. Time-domain adaptive filtering necessitates using only one convergence parameter for all filter coefficients, which may cause slow convergence for some data. Frequency-domain adaptive filtering may solve this problem, since different convergence parameters can be used for different frequency components. This report describes a frequency-domain maximum-likelihood adaptive-filtering algorithm analogous to the time-domain adaptive algorithm. This algorithm was used with a set of synthetic stationary data previously used for a time-domain adaptive-filtering study. Different filter lengths and convergence parameters were used. Results are compared with beamsteer and time-domain adaptive filter. (Author).

Book Efficient Nonlinear Adaptive Filters

Download or read book Efficient Nonlinear Adaptive Filters written by Haiquan Zhao and published by Springer. This book was released on 2023-02-20 with total page 0 pages. 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.

Book Adaptive Filtering

    Book Details:
  • Author : Lino Garcia Morales
  • Publisher : BoD – Books on Demand
  • Release : 2011-09-06
  • ISBN : 9533071583
  • Pages : 414 pages

Download or read book Adaptive Filtering written by Lino Garcia Morales and published by BoD – Books on Demand. This book was released on 2011-09-06 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive filtering is useful in any application where the signals or the modeled system vary over time. The configuration of the system and, in particular, the position where the adaptive processor is placed generate different areas or application fields such as prediction, system identification and modeling, equalization, cancellation of interference, etc., which are very important in many disciplines such as control systems, communications, signal processing, acoustics, voice, sound and image, etc. The book consists of noise and echo cancellation, medical applications, communications systems and others hardly joined by their heterogeneity. Each application is a case study with rigor that shows weakness/strength of the method used, assesses its suitability and suggests new forms and areas of use. The problems are becoming increasingly complex and applications must be adapted to solve them. The adaptive filters have proven to be useful in these environments of multiple input/output, variant-time behaviors, and long and complex transfer functions effectively, but fundamentally they still have to evolve. This book is a demonstration of this and a small illustration of everything that is to come.

Book Adaptive Filtering

    Book Details:
  • Author : Paulo Sergio Ramirez Diniz
  • Publisher : Springer Science & Business Media
  • Release : 2002
  • ISBN : 9781402071256
  • Pages : 594 pages

Download or read book Adaptive Filtering written by Paulo Sergio Ramirez Diniz and published by Springer Science & Business Media. This book was released on 2002 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Filtering: Algorithms and Practical Implementation, Second Edition, presents a concise overview of adaptive filtering, covering as many algorithms as possible in a unified form that avoids repetition and simplifies notation. It is suitable as a textbook for senior undergraduate or first-year graduate courses in adaptive signal processing and adaptive filters. The philosophy of the presentation is to expose the material with a solid theoretical foundation, to concentrate on algorithms that really work in a finite-precision implementation, and to provide easy access to working algorithms. Hence, practicing engineers and scientists will also find the book to be an excellent reference. This second edition contains a substantial amount of new material: -Two new chapters on nonlinear and subband adaptive filtering; -Linearly constrained Weiner filters and LMS algorithms; -LMS algorithm behavior in fast adaptation; -Affine projection algorithms; -Derivation smoothing; -MATLAB codes for algorithms. An instructor's manual, a set of master transparencies, and the MATLAB codes for all of the algorithms described in the text are also available. Useful to both professional researchers and students, the text includes 185 problems; over 38 examples, and over 130 illustrations. It is of primary interest to those working in signal processing, communications, and circuits and systems. It will also be of interest to those working in power systems, networks, learning systems, and intelligent systems.