Digital Signal Processing

Digital Signal Processing
Author :
Publisher : Academic Press
Total Pages : 636
Release :
ISBN-10 : 9780080885261
ISBN-13 : 0080885268
Rating : 4/5 (268 Downloads)

Book Synopsis Digital Signal Processing by : Winser Alexander

Download or read book Digital Signal Processing written by Winser Alexander and published by Academic Press. This book was released on 2016-11-14 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital signal processing (DSP) has been applied to a very wide range of applications. This includes voice processing, image processing, digital communications, the transfer of data over the internet, image and data compression, etc. Engineers who develop DSP applications today, and in the future, will need to address many implementation issues including mapping algorithms to computational structures, computational efficiency, power dissipation, the effects of finite precision arithmetic, throughput and hardware implementation. It is not practical to cover all of these in a single text. However, this text emphasizes the practical implementation of DSP algorithms as well as the fundamental theories and analytical procedures that form the basis for modern DSP applications. Digital Signal Processing: Principles, Algorithms and System Design provides an introduction to the principals of digital signal processing along with a balanced analytical and practical treatment of algorithms and applications for digital signal processing. It is intended to serve as a suitable text for a one semester junior or senior level undergraduate course. It is also intended for use in a following one semester first-year graduate level course in digital signal processing. It may also be used as a reference by professionals involved in the design of embedded computer systems, application specific integrated circuits or special purpose computer systems for digital signal processing, multimedia, communications, or image processing. - Covers fundamental theories and analytical procedures that form the basis of modern DSP - Shows practical implementation of DSP in software and hardware - Includes Matlab for design and implementation of signal processing algorithms and related discrete time systems - Bridges the gap between reference texts and the knowledge needed to implement DSP applications in software or hardware


Digital Signal Processing Related Books

Digital Signal Processing
Language: en
Pages: 636
Authors: Winser Alexander
Categories: Technology & Engineering
Type: BOOK - Published: 2016-11-14 - Publisher: Academic Press

GET EBOOK

Digital signal processing (DSP) has been applied to a very wide range of applications. This includes voice processing, image processing, digital communications,
Digital Signal Processing Algorithms
Language: en
Pages:
Authors: Hari Krishna
Categories:
Type: BOOK - Published: 2017 - Publisher:

GET EBOOK

"Digital Signal Processing Algorithms describes computational number theory and its applications to deriving fast algorithms for digital signal processing. It d
Algorithm Collections for Digital Signal Processing Applications Using Matlab
Language: en
Pages: 200
Authors: E.S. Gopi
Categories: Technology & Engineering
Type: BOOK - Published: 2007-09-20 - Publisher: Springer Science & Business Media

GET EBOOK

The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are presently scattered in different fields. There remains a need to collect a
Digital Signal Processors
Language: en
Pages: 634
Authors: Sen-Maw Kuo
Categories: Technology & Engineering
Type: BOOK - Published: 2005 - Publisher: Prentice Hall

GET EBOOK

This CD contains five appendices from the book and programs (MATLAB, Simulink, C, and TMS320C5000 assembly) with their associated data files.
Fast Algorithms for Signal Processing
Language: en
Pages: 469
Authors: Richard E. Blahut
Categories: Technology & Engineering
Type: BOOK - Published: 2010-06-24 - Publisher: Cambridge University Press

GET EBOOK

Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumptio