Statistics and Adaptive Signal Processing

Author: (USA) Manolakis
Publisher:
Publish Date: 2003-05-01
Features: The main features of this book are: The mathematical descriptions and derivations in the book are limited to the level that senior undergraduate and graduate students can understand, while also being fully understandable for engineering technicians who have studied digital signal processing, probability theory, and linear algebra. Numerous computer experiments are used to illustrate important concepts, making it easier for readers to grasp different theoretical knowledge. Each chapter contains a large number of selected examples and exercises. A set of MATLAB functions is used to solve various technical and real-world problems. This book is one of the latest statistical signal processing textbooks published abroad. Its main feature is to provide a relatively complete discussion and introduction of the theoretical methods, implementation, and applications of statistics and adaptive signal processing. Based on the author's many years of teaching experience and the importance of modern signal processing in theory and application, several key topics such as spectral estimation, signal modeling, adaptive filtering, and array signal processing are discussed in detail. The book emphasizes basic concepts and theoretical methods, aiming to lay a solid foundation for readers to delve into new signal processing topics in the future. To facilitate understanding, the mathematical descriptions and derivations in the book are limited to the level that senior undergraduate, graduate, and engineering technicians can understand, making the book highly practical. This book is suitable for senior undergraduate and graduate students as a teaching reference for elective modern signal processing courses, as well as for engineering technicians as a reference for self-study on modern signal processing theory and applications.