Description
Book SynopsisBased on time-tested course material, this authoritative text examines the key topics, advanced mathematical concepts, and novel analytical tools needed to understand modern communication and radar systems. It covers computational linear algebra theory, VLSI systolic algorithms and designs, practical aspects of chaos theory, and applications in beamforming and array processing, and uses a variety of CDMA codes, as well as acoustic sensing and beamforming algorithms to illustrate key concepts. Classical topics such as spectral analysis are also covered, and each chapter includes a wealth of homework problems. This is an invaluable text for graduate students in electrical and computer engineering, and an essential reference for practitioners in communications and radar engineering.
Trade Review'This book arises from the lifelong teaching of a highly regarded educator with topics of essential foundation to readers of interests to signal processing algorithms. It also contains unique treatments from a respected researcher with an insight one cannot find elsewhere.' K. J. Ray Liu, University of Maryland
'Yao has written an extensive and inclusive book on signal processing, focused on the aspects most relevant to communication and radar systems and based on his teaching and research experience. Beyond being valuable for an advanced course on signal processing, the thoroughness of its mathematical treatment, the inclusion of topics usually not found in textbooks, and the wealth of homework problems, make this book an excellent resource for reference and self-study.' Ezio Biglieri, Universitat Pompeu Fabra
Table of Contents1. Applications of spectral analysis; 2. DFT, FFT, and convolution; 3. Spectral analysis via continuous/discrete fourier transformation; 4. Parametric spectral analysis; 5. Time-frequency spectral analysis; 6. Wavelets and subband decomposition; 7. Beamforming and array processing; 8. Introduction to compressive sampling; 9. Chaotic signal analysis and processing; 10. Computational linear algebra; 11. Applications of LS and SVD techniques; 12. Quantization, saturation, and scaling; 13. Introduction to systolic arrays; 14. Systolic array design by dependence graph mapping; 15. Systolic array processing for least-squares estimation; 16. Systolic algorithms and architectures for communication and radar systems; Index.
