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Qrd-Rls Adaptive Filtering by Jose Apolinario Jr: New

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Last updated on 02 Aug, 2025 10:49:59 BSTView all revisionsView all revisions

Item specifics

Condition
New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Qrd-Rls Adaptive Filtering
Publication Date
2009-02-11
Pages
356
ISBN
9780387097336

About this product

Product Identifiers

Publisher
Springer
ISBN-10
0387097333
ISBN-13
9780387097336
eBay Product ID (ePID)
2442950

Product Key Features

Number of Pages
Xx, 356 Pages
Language
English
Publication Name
Qrd-Rls Adaptive Filtering
Publication Year
2009
Subject
Signals & Signal Processing, Electrical, Telecommunications
Type
Textbook
Subject Area
Technology & Engineering
Author
José Antonio Apolinário Jr.
Format
Hardcover

Dimensions

Item Weight
25.5 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2008-936641
Dewey Edition
22
Reviews
From the reviews: "Starting with a review of the history and the essential concepts in (numerical) linear algebra that are essential in the development of QR decomposition, the book continues with an overview of adaptive filtering techniques, including LMS and RLS algorithms. ... The chapters flow on nicely from one to the other, and the editor is to be congratulated on achieving this. The book is a useful and welcome contribution to the broad topic of numerical linear algebra." (Andrew Dale, Zentralblatt MATH, Vol. 1170, 2009), From the reviews:Starting with a review of the history and the essential concepts in (numerical) linear algebra that are essential in the development of QR decomposition, the book continues with an overview of adaptive filtering techniques, including LMS and RLS algorithms. … The chapters flow on nicely from one to the other, and the editor is to be congratulated on achieving this. The book is a useful and welcome contribution to the broad topic of numerical linear algebra. (Andrew Dale, Zentralblatt MATH, Vol. 1170, 2009), From the reviews: Starting with a review of the history and the essential concepts in (numerical) linear algebra that are essential in the development of QR decomposition, the book continues with an overview of adaptive filtering techniques, including LMS and RLS algorithms. … The chapters flow on nicely from one to the other, and the editor is to be congratulated on achieving this. The book is a useful and welcome contribution to the broad topic of numerical linear algebra. (Andrew Dale, Zentralblatt MATH, Vol. 1170, 2009)
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
621.3815324
Table Of Content
QR Decomposition An Annotated Bibliography.- to Adaptive Filters.- Conventional and Inverse QRD-RLS Algorithms.- Fast QRD-RLS Algorithms.- QRD Least-Squares Lattice Algorithms.- Multichannel Fast QRD-RLS Algorithms.- Householder-Based RLS Algorithms.- Numerical Stability Properties.- Finite and Infinite-Precision Properties of QRD-RLS Algorithms.- On Pipelined Implementations of QRD-RLS Adaptive Filters.- Weight Extraction of Fast QRD-RLS Algorithms.- Linear Constrained QRD-Based Algorithm.
Synopsis
This book provides tools and knowledge in a simple way so that the reader is able to implement a particular QRD-RLS algorithm tailored for the application at hand. The book comprehensively compiles the research of more than a decade into a single publication., 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.
LC Classification Number
TK5102.9

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