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1 Foundations of Computing and Decision Sciences

1 2003

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Adaptive least squares algorithms for two dimensional system identification and filtering: a unified approach

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Glentis G.-O. , Georgoulakis K.

tom Vol. 28, No. 2

95-112

In this paper, a unified approach is presented for adaptive Least Squares Two-Dimensional system identification and linear filtering. First, a unified deterministic Least Squares criterion is introduced, and subsequently utilized for the derivation of a general algorithmic framework for the adaptive Two-Dimensional system identification and filtering. Overdetermined, as well as underdetermined Least Squares Two-Dimensional adaptive algorithms are derived, from the proposed general adaptive scheme. In this way, known Two-Dimensional adaptive algorithms are interpreted as special cases of a general algorithmic form. Moreover, new adaptive algorithms are derived, following the proposed methodology.