Titlebook: Linear Prediction Theory; A Mathematical Basis Peter Strobach Book 1990 Springer-Verlag Berlin Heidelberg 1990 Signal.Signal Processing.alg

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0720-678X e systems. When it is necessary to extract information from a random process, we are frequently faced with the problem of analyzing and solving special systems of linear equations. In the general case these systems are overdetermined and may be characterized by additional properties, such as update

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Book 1990 When it is necessary to extract information from a random process, we are frequently faced with the problem of analyzing and solving special systems of linear equations. In the general case these systems are overdetermined and may be characterized by additional properties, such as update and shift-

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Recursive Least-Squares Using the QR Decomposition, can exploit the recursive properties of the Normal Equations, which we have discussed, to derive recursive O(p.) or even . recursive O(p) algorithms for calculating the updated solution of the Normal Equations at consecutive time steps of observation.

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Book 1990cessor technology, which provide the means to implement linear prediction algorithms, and to operate them in real time. The practical effect is the occurrence of a new class of high-performance adaptive systems for control, communications and system identification applications. This monograph presum

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