Nonlinear Adaptive System Identification Based on Wiener Models (Part 4)

Part of the Signals And Communication Technology book series (SCT)

Having developed the nonlinear Wiener LMS-type adaptive filtering algorithms in the previous three chapters, we show in this chapter that the RLS-type algorithm can be applied for the nonlinear Wiener model too. The trade-off is between convergence rate and computational complexity. In addition, for practical VLSI implementation the inverse QR decomposition for the recursive least squares (RLS-type) algorithm can be combined with the nonlinear Wiener model to achieve a highly efficient systolic array architecture.


Adaptive Filter Subset Selection Systolic Array Recursive Little Square Bilinear System 
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© Springer Science+Business Media, LLC 2007

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