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Digital Signal Processing Fundamentals de Vijay K. Madisetti

Digital Signal Processing Fundamentals: The Digital Signal Processing Handbook, Second Edition

Editat de Vijay K. Madisetti
en Limba Engleză Hardback – 31 oct 2009
Now available in a three-volume set, this updated and expanded edition of the bestselling The Digital Signal Processing Handbook continues to provide the engineering community with authoritative coverage of the fundamental and specialized aspects of information-bearing signals in digital form. Encompassing essential background material, technical details, standards, and software, the second edition reflects cutting-edge information on signal processing algorithms and protocols related to speech, audio, multimedia, and video processing technology associated with standards ranging from WiMax to MP3 audio, low-power/high-performance DSPs, color image processing, and chips on video. Drawing on the experience of leading engineers, researchers, and scholars, the three-volume set contains 29 new chapters that address multimedia and Internet technologies, tomography, radar systems, architecture, standards, and future applications in speech, acoustics, video, radar, and telecommunications.
Emphasizing theoretical concepts, Digital Signal Processing Fundamentals provides comprehensive coverage of the basic foundations of DSP and includes the following parts: Signals and Systems; Signal Representation and Quantization; Fourier Transforms; Digital Filtering; Statistical Signal Processing; Adaptive Filtering; Inverse Problems and Signal Reconstruction; and TimeߝFrequency and Multirate Signal Processing.
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Specificații

ISBN-13: 9781420046069
ISBN-10: 1420046063
Pagini: 922
Ilustrații: 249 b/w images, 31 tables and 1842
Dimensiuni: 180 x 254 x 46 mm
Greutate: 1.72 kg
Ediția:2
Editura: CRC Press
Seriile The Digital Signal Processing Handbook, Second Edition, Digital Signal Processing Handbook, Second Edition

Public țintă

Electrical and computer engineers working in signal processing and advanced undergraduate/graduate students in signal processing courses.

Cuprins

SIGNALS AND SYSTEMS; Vijay K. Madisetti and Douglas B. Williams
 Fourier Methods for Signal Analysis and Processing; W. Kenneth Jenkins
Ordinary Linear Differential and Difference Equations; B.P. Lathi
 Finite Wordlength Effects; Bruce W. Bomar
SIGNAL REPRESENTATION AND QUANTIZATION; Jelena Kovaĉević and Christine Podilchuk
 On Multidimensional Sampling; Ton Kalker
Analog-to-Digital Conversion Architectures; Stephen Kosonocky and Peter Xiao
 Quantization of Discrete Time Signals; Ravi P. Ramachandran
FAST ALGORITHMS AND STRUCTURES; Pierre Duhamel
 Fast Fourier Transforms: A Tutorial Review and State of the Art; Pierre Duhamel and Martin Vetterli
Fast Convolution and Filtering; Ivan W. Selesnick and C. Sidney Burrus
Complexity Theory of Transforms in Signal Processing; Ephraim Feig
Fast Matrix Computations; Andrew E. Yagle
DIGITAL FILTERING; Lina J. Karam and James H. McClellan
Digital Filtering; Lina J. Karam, James H. McClellan, Ivan W. Selesnick, and C. Sidney Burrus
STATISTICAL SIGNAL PROCESSING; Georgios B. Giannakis
Overview of Statistical Signal Processing; Charles W. Therrien
Signal Detection and Classification; Alfred Hero
Spectrum Estimation and Modeling; Petar M. Djurić and Steven M. Kay
 Estimation Theory and Algorithms: From Gauss to Wiener to Kalman; Jerry M. Mendel
Validation, Testing, and Noise Modeling; Jitendra K. Tugnait
Cyclostationary Signal Analysis; Georgios B. Giannakis
ADAPTIVE FILTERING; Scott C. Douglas
Introduction to Adaptive Filters; Scott C. Douglas
Convergence Issues in the LMS Adaptive Filter; Scott C. Douglas and Markus Rupp
Robustness Issues in Adaptive Filtering; Ali H. Sayed and Markus Rupp
Recursive Least-Squares Adaptive Filters; Ali H. Sayed and Thomas Kailath
Transform Domain Adaptive Filtering; W. Kenneth Jenkins, C. Radhakrishnan, and Daniel F. Marshall
Adaptive IIR Filters; Geoffrey A. Williamson
Adaptive Filters for Blind Equalization; Zhi Ding
INVERSE PROBLEMS AND SIGNAL RECONSTRUCTION; Richard J. Mammone
Signal Recovery from Partial Information; Christine Podilchuk
Algorithms for Computed Tomography; Gabor T. Herman
Robust Speech Processing as an Inverse Problem; Richard J. Mammone and Xiaoyu Zhang
Inverse Problems, Statistical Mechanics, and Simulated Annealing; K. Venkatesh Prasad
Image Recovery Using the EM Algorithm; Jun Zhang and Aggelos K. Katsaggelos
Inverse Problems in Array Processing; Kevin R. Farrell
Channel Equalization as a Regularized Inverse Problem; John F. Doherty
Inverse Problems in Microphone Arrays; A.C. Surendran
Synthetic Aperture Radar Algorithms; Clay Stewart and Vic Larson
Iterative Image Restoration Algorithms; Aggelos K. Katsaggelos
TIMEߝFREQUENCY AND MULTIRATE SIGNAL PROCESSING; Cormac Herley and Kambiz Nayebi
Wavelets and Filter Banks; Cormac Herley
Filter Bank Design; Joseph Arrowood, Tami Randolph, and Mark J.T. Smith
Time-Varying Analysis-Synthesis Filter Banks; Iraj Sodagar
Lapped Transforms; Ricardo L. de Queiroz
INDEX

Notă biografică

Vijay K. Madisetti is a professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology in Atlanta. He teaches graduate and undergraduate courses in digital signal processing and computer engineering, and leads a strong research program in digital signal processing, telecommunications, and computer engineering. Dr. Madisetti received his BTech (Hons) in electronics and electrical communications engineering in 1984 from the Indian Institute of Technology, Kharagpur, India, and his PhD in electrical engineering and computer sciences in 1989 from the University of California at Berkeley. He has authored or edited several books in the areas of digital signal processing, computer engineering, and software systems, and has served extensively as a consultant to industry and the government. He is a fellow of the IEEE and received the 2006 Frederick Emmons Terman Medal from the American Society of Engineering Education for his contributions to electrical engineering.