Higher Order Statistics
Purpose In this chapter, we present a few basic notions about higher order statistics that generalise notions defined above for second order statistics. We show, in particular, how the definition of the spectral representation of a process can be generalised for processes that are stationary at orders higher than two.
KeywordsARMA Model High Order Statistics Cumulant Function Autocovariance Function Inverse Filter
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- 1.The Kronecker product of two matrices A and B of respective size m a x n a and m b x n b is the matrix A ⊗ B of size m a m b x n a n b, with general term [A ⊗ B]ima+k,jna+l = [A]ij[B]kl.Google Scholar