Properties of the structured auto-regressive time-frequency distribution

Author

Ängeby, Jakob

Author_Institution

Dept. of Appl. Electron Phys., Chalmers Univ. of Technol., Goteborg, Sweden

Volume

3

fYear

1997

fDate

21-24 Apr 1997

Firstpage

2017

Abstract

Primarily the structured auto-regressive (AR) model was introduced as a means to estimate the parameters of non-stationary signals in additive noise. However, it is straightforward to use the structured AR model as a model-based time-frequency distribution (TFD). It is shown that the structured AR TFD can be interpreted as a member of Cohen´s (1989) class with a non-stationary adaptive kernel. The interpretation of the structured AR TFD as a member of Cohen´s class establishes a link between TFD:s and signal parameter estimation

Keywords

Gaussian noise; adaptive filters; adaptive signal detection; adaptive signal processing; autoregressive processes; filtering theory; parameter estimation; spectral analysis; statistical analysis; time-frequency analysis; white noise; AWGN; Cohen´s class; additive noise; nonstationary adaptive kernel; nonstationary signals; signal parameter estimation; spectral density; structured AR filter; structured AR time-frequency distribution; structured autoregressive model; Additive noise; Filters; Fourier transforms; Integrated circuit modeling; Kernel; Parameter estimation; Signal design; Signal processing; Signal resolution; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on

Conference_Location

Munich

ISSN

1520-6149

Print_ISBN

0-8186-7919-0

Type

conf

DOI

10.1109/ICASSP.1997.599318

Filename

599318