High-performance CORDIC Based Orthogonal Recursive and Adaptive Filtering PDF Download

Author: Chʻun Ma
Publisher:
ISBN:
Category :
Languages : en
Pages : 384

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Author: JOSE APOLINARIO JR
Publisher: Springer Science & Business Media
ISBN: 0387097341
Category : Technology & Engineering
Languages : en
Pages : 359

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Book Description
I feel very honoured to have been asked to write a brief foreword for this book on QRD-RLS Adaptive Filtering–asubjectwhichhas been close to my heart for many years. The book is well written and very timely – I look forward personally to seeing it in print. The editor is to be congratulated on assembling such a highly esteemed team of contributing authors able to span the broad range of topics and concepts which underpin this subject. In many respects, and for reasons well expounded by the authors, the LMS al- rithm has reigned supreme since its inception, as the algorithm of choice for prac- cal applications of adaptive ltering. However, as a result of the relentless advances in electronic technology, the demand for stable and ef cient RLS algorithms is growing rapidly – not just because the higher computational load is no longer such a serious barrier, but also because the technological pull has grown much stronger in the modern commercial world of 3G mobile communications, cognitive radio, high speed imagery, and so on.

Author: Leonardo Rey Vega
Publisher: Springer Science & Business Media
ISBN: 3642302998
Category : Technology & Engineering
Languages : en
Pages : 128

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Book Description
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.

Author: Kalavai Janardhan Raghunath
Publisher:
ISBN:
Category :
Languages : en
Pages : 386

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Author: Weifeng Liu
Publisher: John Wiley & Sons
ISBN: 1118211219
Category : Science
Languages : en
Pages : 167

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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.

Author:
Publisher:
ISBN:
Category : Electrical engineering
Languages : en
Pages : 1360

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Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 51

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Discrete orthogonal functions are used in adaptive system identification algorithms. Adaptive filters are realized by forming linear combinations of discrete Legendre, Laguerre, and Jacobi polynomials, and backward prediction-error polynomials from a lattice structure. The adaptive filter weights are updated using the LMS algorithm. FIR and IIR bandpass filters are modeled using the adaptive filters, and performance comparisons are made.

Author: Institute of Electrical and Electronics Engineers
Publisher:
ISBN:
Category : Electric engineering
Languages : en
Pages : 1234

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Issues for 1973- cover the entire IEEE technical literature.

Author:
Publisher:
ISBN:
Category : Electrical engineering
Languages : en
Pages : 1860

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Author: K. J. Ray Liu
Publisher: Wiley-IEEE Press
ISBN:
Category : Mathematics
Languages : en
Pages : 704

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Book Description
Electrical Engineering/Signal Processing High-Performance VLSI Signal Processing Innovative Architectures and Algorithms Volume 2 Systems Design And Applications The second volume in a two-volume set, High-Performance VLSI Signal Processing: Innovative Architectures and Algorithms brings together the most innovative papers in the field, focused introductory material, and extensive references. The editors present timely coverage of the latest design tools, design environments, and implementations of VLSI signal processing systems. These volumes will serve as vital resources for engineers who want a comprehensive knowledge of the extremely interdisciplinary field of high-performance VLSI processing. The editors provide a practical understanding of the merits of total system design through an insightful, synergistic presentation of methodology, architecture, and infrastructure. Each volume features: Major papers that span the wide range of research areas in the field Chapter introductions including historical perspectives Numerous applications-oriented design examples Coverage of current and future technological trends