Nonminimum-phase complex Fourier series based model for statistical signal processing

Author

Chen, Ching-Yung ; Chi, Chong-Yung

Author_Institution

Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan

fYear

1999

fDate

1999

Firstpage

30

Lastpage

33

Abstract

In this paper, a parametric complex Fourier series based model (FSBM), an extension of the real FSBM proposed by Chi, for or as an approximation to an arbitrary nonminimum-phase complex linear time-invariant (LTI) system is proposed for statistical signal processing applications where signals and LTI systems of interest are complex. Based on the proposed complex FSBM, a complex linear prediction error (LPE) filter is presented along with the Cramer Rao (CR) bound for the case of finite Gaussian measurements. Then an MP-AP algorithm is presented for the estimation of the complex FSBM parameters followed by some simulation results for channel identification and equalization in communications

Keywords

Fourier series; Gaussian distribution; equalisers; linear systems; parameter estimation; prediction theory; signal processing; statistical analysis; Cramer Rao bound; Fourier series-based model; LPE filter; LTI system; MP-AP algorithm; channel equalization; channel identification; complex linear prediction error; finite Gaussian measurements; linear time-invariant system; nonminimum-phase complex model; parameter estimation; parametric complex model; simulation; statistical signal processing; Fourier series; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on

Conference_Location

Caesarea

Print_ISBN

0-7695-0140-0

Type

conf

DOI

10.1109/HOST.1999.778686

Filename

778686