DocumentCode :
891179
Title :
Waveform estimation from noisy signals with variable signal delay using bispectrum averaging
Author :
Nakamura, Masahiko
Author_Institution :
Div. of Human Structure & Function, Tokai Univ. Sch. of Med., Ischara, Japan
Volume :
40
Issue :
2
fYear :
1993
Firstpage :
118
Lastpage :
127
Abstract :
A technique based on bispectrum averaging is described for generally recovering the signal waveform from a set of noisy signals with variable signal delay. The technique does not require explicit time alignment of signals and any initial estimate of signal. The technique, however, does not yield estimates of the signal position. A comparison is made of two algorithms for recovering the Fourier amplitude and the Fourier phase from an averaged bispectrum. These algorithms are the recursive method and the least squares method. The methods are numerically investigated using computer-generated data and a physiological signal and noise. The advantages and disadvantages of these different algorithms are discussed. Some experimental results for the evoked potential studies that demonstrate the technique are given. The results show the effectiveness of the technique: various potential applications of the technique might be expected.
Keywords :
bioelectric potentials; electroencephalography; medical signal processing; Fourier amplitude; Fourier phase; algorithms; bispectrum averaging; computer-generated data; noisy signals; signal position; signal waveform recovery; signals alignment; variable signal delay; Adaptive filters; Application software; Biomedical engineering; Delay estimation; Electroencephalography; Least squares methods; Noise generators; Propagation delay; Signal generators; Signal to noise ratio; Yield estimation; Algorithms; Artifacts; Computer Simulation; Evaluation Studies as Topic; Evoked Potentials; Fourier Analysis; Humans; Least-Squares Analysis; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.212065
Filename :
212065
Link To Document :
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