訊號與系統

Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech. Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical bases, requirements for estimation and detailed quantitative examples for implementing techniques for classical signal analysis. This book will help readers understand real-world applications of signal analysis as they relate to biomedical engineering. The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically.

Richard Shiavi, Vanderbilt University, Nashville, Tennessee, U.S.A.

Introduction to Terminology;
Empirical Modeling and Approximation;
Fourier Analysis; Probability Concepts and Signal Characteristics;
Random Processes and Signal Correlation;
Random Signals, Linear Systems, and Power Spectra;
Spectral Analysis for Random Signals;
Random Signal Modeling and Modern Spectral Estimation;
Theory and Application of Cross Correlation and Coherence