Digital spectral analysis with applications

TLDR: In this article, a broad perspective of spectral estimation techniques and their implementation is provided, focusing on spectral estimation of discretespace sequences derived by sampling continuous space signals, including parametric methods, minimum variance method, eigenanalysis-based estimators, multichannel methods, and twodimensional methods.

Abstract: This new book provides a broad perspective of spectral estimation techniques and their implementation. It concerned with spectral estimation of discretespace sequences derived by sampling continuousspace signals. Among its key features, the book: · Emphasizes the behavior of each spectral estimator for short data records. · Provides 35 computer programs, including fast algorithms. · Provides the theoretical background and review material in linear systems, Fourier transforms matrix algebra, random processes, and statics. · Summarizes classical spectral estimation as it is practiced today. · Covers Prony’s method, parametric methods, the minimum variance method, eigenanalysis-based estimators, multichannel methods, and twodimensional methods. · Includes problems. · Contains appendices that cover Sunspot Numbers, Complex Test Data, Temperature Data, and Program Conversion for Complex-to-Real Case. Of Special Interest A disk is included that has a double-sides 360kB format readable by any personal computer with an MS-DOS 2 or 3 operating system, such as the IBM XT or AT.