Statistical signal processing algorithms

Author: (USA) Proakis (Proakis/J.G.) et al. / Tang Jun et al.
Publisher:
Publish Date: 2006-03-01
Features: This book aims to research high-performance practical algorithms in fields such as modern power spectrum estimation, adaptive signal processing, and adaptive array signal processing. The original authors are all distinguished scholars in this field. The book demonstrates the authors' unique craftsmanship in both depth and breadth, as well as in the organization and selection of materials and content. It systematically presents the fundamental theories and technological developments of statistical signal processing algorithms, including fast algorithms for computing convolution and discrete Fourier transforms, linear prediction and optimal Wiener filters, filter design based on the least squares method, single-channel adaptive filter algorithms based on the LMS algorithm and recursive least squares sixth-order algorithm, power spectrum estimation, and high-order statistical methods in signal modeling and system identification. Exercises and practical content are provided at the end of each chapter. The Chinese translation is performed by senior researchers and teachers from Tsinghua University. The book is well-organized, covering various new technologies and theories in the field of statistical signal processing algorithms. It can serve as a textbook for information engineering and communication-related majors in higher education institutions, as well as a reference for researchers in fields such as communication, speech, image, and radar.