Plant identification via adaptive combination of transversal filters
Signal Processing - Signal processing in UWB communications
Gain allocation in proportionate-type NLMS algorithms for fast decay of output error at all times
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
EURASIP Journal on Advances in Signal Processing
Proportionate adaptive algorithms for network echo cancellation
IEEE Transactions on Signal Processing
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Recently, we have proposed three schemes for gain allocation in proportionate-type NLMS algorithms for fast decay at all time. The gain allocation schemes are based on: (1) maximization of one-step decay of the mean square output error, (2) maximization of one-step conditional probability density for true weight values, and (3) adaptation of µ-law for compression of weight estimates using the output square error. Scheme (1) implies sorting and time consuming calculations that can restrict its ability to work in real-time. We will propose usage of computationally simplified schemes and show that the loss in performance is negligible. Scheme (3) needs calculation of a logarithmic function that we will replace by calculation of a piecewise linear function and show that there is no significant loss in performance. Schemes (1) and (2) use fast-converging biased estimates to calculate gain allocation. The performance deterioration because of the biased estimates is especially noticeable in the steady-state regime. We are going to consider combining the fast-converging biased estimates with slow-converging unbiased estimates. The combination will be related to the magnitude of the output square error. Comparison between the original and modified algorithms in sparse echo-cancellation scenarios will be presented for white input, color input, and voice inputs.