Abstract

A fast sliding window QRD-RLS algorithm is proposed. “Fast” means that for the pth-order system we need only O( p) operations at each iteration. This is derived by using Proudler's method of relating an adaptive filter problem to two linear prediction problems and transforming the corresponding signal-flow-graphs. A “sliding window” is used to restrict the size of the data matrix. To do so, we delete the oldest data after attaching a new one. For these two steps the Givens rotations and the stabilized hyperbolic rotation are used. Finally, it is shown by computer simulations that this new algorithm has high performance for convergence and good stability in case where the system is rapidly changing.

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