Abstract
A novel dynamic-based deconvolution (DBD) algorithm is presented that can be exploited in blind channel estimation as well as in telephony echo cancellation. Chaotic coded signals generated by the logistic map are employed while the channel is represented by an autoregressive model. The applicability is demonstrated in a speech transmission scenario using chaotic coded speech showing a modeling misadjustment improvement of 24 dB/100 iterations which is sixfold that obtained by the LMS for a 128 tap digital adaptive filter driven by ideal white Gaussian noise excitation.
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