Performance analysis of a crosstalk resistant adaptive noise canceller

The Adaptive Noise Canceller (ANC) is a commonly used adaptive filter for estimating signal in additive noise. An important factor that effects the performance of the ANC is the signal crosstalk between the primary and reference channels of the ANC. This results in reduced output Signal-to-Noise Rat...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems. 2, Analog and digital signal processing Analog and digital signal processing, 1996-07, Vol.43 (7), p.473-482
Main Authors: Parsa, V., Parker, P.A., Scott, R.N.
Format: Article
Language:English
Subjects:
Adaptive filters
Additive noise
Applied sciences
Crosstalk
Detection, estimation, filtering, equalization, prediction
Distortion
Exact sciences and technology
Information, signal and communications theory
Interference
Muscles
Noise cancellation
Performance analysis
Signal and communications theory
Signal design
Signal to noise ratio
Signal, noise
Telecommunications and information theory
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Summary:The Adaptive Noise Canceller (ANC) is a commonly used adaptive filter for estimating signal in additive noise. An important factor that effects the performance of the ANC is the signal crosstalk between the primary and reference channels of the ANC. This results in reduced output Signal-to-Noise Ratios (SNR's) and undesirable signal distortion. A Crosstalk Resistant Adaptive Noise Canceller (CRANC), which is a cascade of two ANC's, can be designed to output a distortion free signal. This paper undertakes the performance analysis of the CRANC filter under the influence of various parameters. It is shown that the CRANC's performance is sensitive to the presence of uncorrelated noise sources. Equations are derived to show the effect of uncorrelated noise sources on the CRANC filter structure. The CRANC's performance in estimating the stimulus evoked nerve signal embedded in larger muscle interference is then evaluated through simulations. The results show that with no or little uncorrelated noise present, the CRANC gives a superior performance compared to the ANC. With higher levels of uncorrelated noise power, however, the CRANC's performance is shown to be comparable to that of the ANC. An alternate multichannel CRANC structure is then utilized to mitigate the effects of the uncorrelated noise sources, and its performance in estimating the nerve signal from the muscle interference is evaluated through simulations.
ISSN:1057-7130
1558-125X
DOI:10.1109/82.508423