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Prediction of a noise-distorted, multivariate, non-stationary signal

Published online by Cambridge University Press:  14 July 2016

Eugene Sobel*
Affiliation:
Stanford University

Extract

This paper deals with the problem of predicting or extracting a certain type of non-stationary sequence or signal from another sequence composed of the signal and a stationary noise. The noise is assumed to be uncorrelated with the signal. Although all sequences in the body of this paper are multivariate, for purposes of discussion, this introduction will deal with only the univariate case.

Type
Research Papers
Copyright
Copyright © Sheffield: Applied Probability Trust 

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