A fast digital method of estimating the autocorrelation of a Guassian stationary process

Author

Hertz, David

Author_Institution

Technion-Israel Institute of Technology, Haifa, Israel

Volume

Issue

fYear

1982

fDate

4/1/1982 12:00:00 AM

Firstpage

329

Lastpage

329

Abstract

Given a zero mean stationary Gaussian process ${x_{n}}$ , it is shown that the autocorrelation can be estimated by $\\hat{R}_{xx}(j) = C_{N} \\sum \\min{i=1}\\max {N} x_{i} sign(x_{i+j})$ where $C_{N}=frac{\\pi}{2N^{2}} \\sum \\min{i=1}\\max {N}|x_{i}|$ . This method is attractive since $C_{N}$ needs to he Computed only once, and $\\sum \\min{i=1}\\max {N} x_{i} sign (x_{i+j})$ can be computed by additions only. Moreover, the shape of the autocorrelation given by $\\hat{R}_{xx}(j)/C_{N}$ can be computed by additions only.

Keywords

Adaptive filters; Adaptive signal processing; Autocorrelation; Entropy; Gaussian processes; Least squares approximation; Noise cancellation; Shape; Spectral analysis; Speech processing;

fLanguage

English

Journal_Title

Acoustics, Speech and Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

0096-3518

Type

jour

DOI

10.1109/TASSP.1982.1163885

Filename

1163885

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1098765