Analysis of periodic signals via order statistic filters

Author

Longbotham, Harold G. ; Arnow, Tom ; Barsalou, Norman ; Keating, Jerome ; Glockman, R.D.

Author_Institution

Texas Univ., San Antonio, TX, USA

fYear

1990

fDate

1-3 May 1990

Firstpage

2128

Abstract

The authors set forth an approach to the robust analysis of periodic digital data. This approach uses optimal order statistic (OS) filters for the filtering of non-Gaussian additive i.i.d. (independently identically distributed) noise and OS and generalized order statistic (GOS) filters to factor out impulsive and/or bursty noise. The noise is not necessarily stationary and may vary with phase (amplitude) and/or time. The methodology is applied to visual evoked response data

Keywords

bioelectric potentials; digital filters; filtering and prediction theory; noise; signal processing; statistical analysis; FIR; bursty noise; generalised order statistic filters; impulsive noise; independently identically distributed noise; nonGaussian additive noise; optimal order statistic filters; periodic digital data; periodic signals; robust analysis; time varying noise; visual evoked response data; Additive noise; Digital signal processing; Finite impulse response filter; Frequency; Least squares approximation; Noise robustness; Nonlinear filters; Signal analysis; Statistical analysis; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1990., IEEE International Symposium on

Conference_Location

New Orleans, LA

Type

conf

DOI

10.1109/ISCAS.1990.112233

Filename

112233