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Classification of Data under Autoregressive Circulant Covariance
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The problem of classification is an old one that has§application in geophysical, medical, signal§processing and many other fields. There are numerous§approaches to this problem using the statistical§properties of the populations from which observations§are drawn. In applications such as geophysical and§signals processing there is a natural structure on§the variance-covariance matrix of the observation§vectors. The efficacy of classification is generally§increased by taking that structure into account. One§such structure that is used to model that§variance-covariance matrix is the autoregressive§circulant (ARC) structure. In this book,§classification rules are derived using the assumption§of such a structure. Techniques to compute these§rules are discussed and their efficacy studied.
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