Title :
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
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;
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
DOI :
10.1109/ISCAS.1990.112233
