A new strategy for noise reduction of fast fading channel is presented. Firstly, more information is acquired utilizing the reconstructed embedding phase space. Then, based on the Recurrent Least Squares Sup-port Vector Machines (RLS-SVM), noise reduction of the fast fading channel is realized. This filtering tech-nique does not make use of the spectral contents of the signal. Based on the stability and the fractal of the cha-otic attractor, the RLS-SVM algorithm is a better candidate for the nonlinear time series noise-reduction. The simulation results shows that better noise-reduction performance is acquired when the signal to noise ratio is 12dB.
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