Higher-order spectrum estimation via noncausal autoregressive modeling and deconvolution

Author

Nikias, Chrysostomos L. ; Chiang, Hsing-Hsing

Author_Institution

Commun. & Digital Signal Process. Center, Northeastern Univ., Boston, MA, USA

Volume

36

Issue

12

fYear

1988

fDate

12/1/1988 12:00:00 AM

Firstpage

1911

Lastpage

1913

Abstract

A method for nonminimum-phase finite impulse response (FIR) system identification is introduced that is based on noncausal autoregressive (AR) modeling of the third moments of the output data. The magnitude and phase response of the FIR system are expressed in terms of the parameters of a noncausal AR model. The set of AR parameters is obtained by solving an overdetermined linear system of equations that is formed using third-moment estimates of the output data. The performance of the method is illustrated with simulation examples

Keywords

identification; signal processing; spectral analysis; FIR; deconvolution; noncausal autoregressive modelling; nonminimum-phase finite impulse response; overdetermined linear system; spectrum estimation; system identification; third-moment estimates; Deconvolution; Digital signal processing; Estimation error; Finite impulse response filter; Frequency; Narrowband; Nonuniform sampling; Sampling methods; Signal processing; Spectral analysis;

fLanguage

English

Journal_Title

Acoustics, Speech and Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

0096-3518

Type

jour

DOI

10.1109/29.9037

Filename

9037