Structured Linear Algebra Problems in Digital Signal Processing
In this paper we give a survey of a number of linear algebra problems occurring in digital signal processing, where the structure of the matrices involved is crucial. Although the problems one wants to solve for these matrices are rather classical, one can not make use anymore here of standard linear algebra tools, since the structure of the matrices has to be taken into account. We discuss in this paper some of these problems and show how structure affects the sensitivity of the problem at hand and how algorithms should be adapted in order to cope with the structure constraint.
KeywordsCovariance Autocorrelation Convolution Trench Dition
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