Author : Robert Jeffrey Keeler
Publisher :
ISBN 13 :
Total Pages : 188 pages
Book Rating : 4.3/5 (126 download)
Book Synopsis Adaptive Frequency Estimation and New Convergence Properties for the Least Mean Square Algorithm by : Robert Jeffrey Keeler
Download or read book Adaptive Frequency Estimation and New Convergence Properties for the Least Mean Square Algorithm written by Robert Jeffrey Keeler and published by . This book was released on 1980 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The convergence properties of the least mean square (LMS) algorithm are interpreted in terms of a vector space associated with the coefficients of the adaptive linear prediction filter (ALPF). Signal planes defined in this weight vector space are used to describe the frequency tracking by characteristics of spectral estimators based on the ALPF and are used to explain the effects of both the filter parameters and the algorithm on tracking speed. The performances of three different adaptive frequency estimators derived from the ALPF are compared. Two of these employ Fourier transforms of the coefficients and the third is based on a transform of the ALPF output. Comparisons with the conventional periodogram spectrum estimator are presented in terms of a signal-to-noise ratio (SNR) defined in frequency domain parameters. Specific calculations for one ALPF frequency estimator (The maximum entropy estimator) are used to demonstrate a bias in this estimator.