DocumentCode
1213695
Title
High-Resolution Alignment of Sampled Waveforms
Author
McGill, Kevin C. ; Dorfman, Leslie J.
Author_Institution
Department of Neurology, Stanford University School of Medicine, Stanford, CA 94305, and the Rehabilitative Research and Development Center, Palo Alto Veterans Administration Medical Center
Issue
6
fYear
1984
fDate
6/1/1984 12:00:00 AM
Firstpage
462
Lastpage
468
Abstract
Waveforms are often sampled faster than the Nyquist rate to obtain desired temporal resolution, even though, theoretically, oversampling adds no information and should not be necessary. This paper shows how high resolution can be achieved efficiently from data sampled at the Nyquist rate by working with coefficients of the Fourier-series expansion of the continuous interpolating waveform. Practical algorithms are presented for aligning and comparing waveforms, locating peaks, resolving superimpositions, and averaging overlapping waveforms. The algorithms prove to be more accurate, and to require fewer computations and less storage than techniques which employ continuous oversampling in many signal-processing applications, particularly template matching.
Keywords
Computational efficiency; Digital filters; Electromyography; Low-frequency noise; Noise level; Noise reduction; Sampling methods; Signal resolution; Signal to noise ratio; Thumb; Electromyography; Humans; Information Theory; Motor Neurons;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.1984.325413
Filename
4121865
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