A Rapid Introduction to Adaptive Filtering (Record no. 55476)
[ view plain ]
000 -LEADER | |
---|---|
fixed length control field | 03292nam a22005415i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-642-30299-2 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200421111839.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 120803s2013 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783642302992 |
-- | 978-3-642-30299-2 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 621.382 |
100 1# - AUTHOR NAME | |
Author | Vega, Leonardo Rey. |
245 12 - TITLE STATEMENT | |
Title | A Rapid Introduction to Adaptive Filtering |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XII, 122 p. 23 illus. |
490 1# - SERIES STATEMENT | |
Series statement | SpringerBriefs in Electrical and Computer Engineering, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Wiener Filtering and examples -- Steepest descent procedure -- Stochastic gradient adaptive filtering: LMS (Least Mean Squares), NLMS (Normalized Mean Squares) -- Sign-error algorithm, APA (Affine Projection Algorithms) -- Convergence results -- Applications -- LS (Least Squares) and RLS (Recursive Least Squares) -- Computational complexity and fast implementations -- Applications. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
700 1# - AUTHOR 2 | |
Author 2 | Rey, Hernan. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-642-30299-2 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Berlin, Heidelberg : |
-- | Springer Berlin Heidelberg : |
-- | Imprint: Springer, |
-- | 2013. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational intelligence. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Signal, Image and Speech Processing. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence (incl. Robotics). |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational Intelligence. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2191-8112 |
912 ## - | |
-- | ZDB-2-ENG |
No items available.