We derive a new RLS algorithm: the generalized sliding window RLS (GSWRLS) algorithm and its fast numerically stabilized version: the GSW SFTF algorithm. The generalised window used consists of an exponential decay with base /spl lambda/ for the first L lags, a decrease by a factor 1-/spl alpha/ at lag L, and a further exponential decay with base /spl lambda/ beyond lag L. The exponential and rectangular windows are special cases of the generalized window. We analyze the steady-state excess mean squared error components due to the estimation noise and lag noise with different models for the time-varying optimal filter coefficients. This analysis shows that the exponential window performs better than the rectangular window, but also that the optimal generalized windows performs even better.
Performance analysis and FTF version of the generalized sliding window recursive least-squares (GSWRLS) algorithm
Asilomar 1995, 29th IEEE Annual Asilomar Conference on Signals, Systems and Computers, October 30-November 2nd, 1995, Pacific Grove, USA
Systèmes de Communication
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