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.
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 Time–Frequency and Multirate Signal Processing.
Signals and Systems. Signal Representation and Quantization. Fast Algorithms and Structures. Digital Filtering. Statistical Signal Processing. Adaptive Filtering. Inverse Problems and Signal Reconstruction. Time–Frequency and Multirate Signal Processing. Index.
Drawing from the knowledge, experience, and insight of leading engineers, researchers, and scholars in the field, Digital Signal Processing Fundamentals is one of three self-contained volumes in the new Digital Signal Processing Handbook, Second Edition. Emphasizing theoretical concepts, this volume 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 Time–Frequency and Multirate Signal Processing.
Praise for the previous edition:
An excellent compendium of theoretical topics in DSTP ... a one-stop shop of technical information on digital signal processing. ... This book has saved me days in independent research.
—Howard Rubin, on Amazon.com
A useful handbook for the professional as well as for graduate students and faculty.—E. A. Hoyer, Wichita State University, in CHOICE, Vol. 36, No. 1
Emphasizing theoretical concepts, this title 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; and, Inverse Problems and Signal Reconstruction.
Über den Autor
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.
Inhaltsverzeichnis
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 Kovacevic 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. Djuric 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 TIME-FREQUENCY 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
Klappentext
Emphasizing theoretical concepts, this title 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; and, Inverse Problems and Signal Reconstruction.
