Spectrum analysis A modern perspective

This Article covers the main topic of Spectrum analysis and will use as a base to my main research.

Abstract:

A summary of many of the new techniques developed in the last two decades for spectrum analysis of discrete time series is presented in this tutorial. An examination of the underlying time series model assumed by each technique serves as the common basis for understanding the differences among the various spectrum analysis approaches. Techniques discussed include the classical periodogram, classical Blackman-Tukey, autoregressive (maximum entropy), moving average, autotegressive-moving average, maximum likelihood, Prony, and Pisarenko methods. A summary table in the text provides a concise overview for all methods, including key references and appropriate equations for computation of each spectral estimate.

Link to Article:

Author(s) Kay, S.M. University of Rhode Island, Kingston, RI Marple, S.L., Jr.

ISSN : 0018-9219Date of Current Version :28 June 2005Digital Object Identifier : 10.1109/PROC.1981.12184