The Regularized Adaline Learning Algorithm for the Problem of Evaluation of Non-Stationary Parameters

[1]  J. Nagumo,et al.  A learning method for system identification , 1967, IEEE Transactions on Automatic Control.

[2]  S. Kaczmarz Approximate solution of systems of linear equations , 1993 .

[3]  Jacob Benesty,et al.  On Regularization in Adaptive Filtering , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[4]  Bernard Widrow,et al.  30 years of adaptive neural networks: perceptron, Madaline, and backpropagation , 1990, Proc. IEEE.

[5]  Patrick A. Naylor,et al.  Selective-Tap Adaptive Filtering With Performance Analysis for Identification of Time-Varying Systems , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[6]  Jacob Benesty,et al.  An optimized NLMS algorithm for system identification , 2016, Signal Process..

[7]  C.F.N. Cowan,et al.  Performance comparison of RLS and LMS algorithms for tracking a first order Markov communications channel , 1990, IEEE International Symposium on Circuits and Systems.

[8]  Jacob Benesty,et al.  An overview on optimized NLMS algorithms for acoustic echo cancellation , 2015, EURASIP J. Adv. Signal Process..

[9]  V. Dupac A DYNAMIC STOCHASTIC APPROXIMATION METHOD , 1965 .

[10]  Kevin T. Wagner,et al.  Towards analytical convergence analysis of proportionate-type nlms algorithms , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.