Statistical signal processing algorithms

Author: John G. Proakis
Publisher:
Publish Date: 2003-01-01
Features: This book comprehensively and systematically introduces various main algorithms in the field of digital signal processing. The book is divided into 9 chapters, including Introduction, Convolution and Discrete Fourier Transform Algorithms, Linear Prediction and Wiener Filtering, Least Squares Methods for System Modeling and Identification, Adaptive Filters, Recursive Least Squares Fast Algorithms for Multichannel Signals, Parameter and Non-Parameter Power Spectrum Algorithms, Signal Modeling and System Identification Using High-Order Statistics, and more. The book presents novel and comprehensive content, summarizing many technical theories in digital signal processing technology and thoroughly discussing important research directions. It is an important book in the field of digital signal processing today. Exercises are provided at the end of some chapters for easy learning. The book can serve as a textbook for senior undergraduate or graduate students in the field of digital signal processing, as well as for those in related fields.