Digital Spectral Analysis: Second Edition
by S. Lawrence Marple, Jr.
Digital Spectral Analysis: Second Edition offers a broad perspective of signal temporal modeling and spectral estimation techniques and their practical implementation. Coverage includes spectral estimation of discrete-time or discrete-space signals, typically derived by sampling continuous-time or continuous-space signals. A systematic approach via signal modeling emphasizes the behavior of each spectral estimator for short data records in the context of each estimator’s signal model. The text describes over forty techniques that have been implemented as MATLAB functions. Most of these are implemented with fast computational algorithms that are difficult to find in the literature. Demonstration MATLAB scripts are available to illustrate techniques from the key chapters so that readers can experience the signal analysis techniques of those chapters without an investment in the chapter mathematics.
In addition to summarizing classical Fourier-based and alternative higher-resolution spectral estimation, this text provides tutorial review chapters in linear systems, Fourier transforms, matrix algebra, and random processes. Temporal and spectral estimators covered include FFT-based methods, parametric methods (autoregressive, moving average), exponential signal models (Prony’s method), minimum variance spectral estimation, and eigenanalysis-based frequency estimators. The text extends many of these estimators to multichannel methods and two-dimensional methods, which also have been implemented in MATLAB. Although the text and associated software is designed to provide rapid implementation for spectral analysis of signal or data from any engineering or scientific discipline, the text has mathematical depth that is also suitable for advanced undergraduate and graduate courses in electrical engineering and statistics. Problems are available for course studies. |
