Title :
A stochastic Newton algorithm with data-adaptive step size
Author :
Davila, Carlos E.
Author_Institution :
Dept. of Electr. Eng., Southern Methodist Univ., Dallas, TX, USA
fDate :
10/1/1990 12:00:00 AM
Abstract :
A stochastic Newton algorithm for adaptive filtering which is a generalization of the so-called normalized least mean-square algorithm is proposed. Expressions for the expected value of the algorithm weight error vector and second moment of the weight error-vector norm are derived, and have been verified by computer simulation. Experimental results which demonstrate the improved convergence of the algorithm over the algorithm after a large number of iterations are given
Keywords :
convergence; filtering and prediction theory; least squares approximations; stochastic processes; adaptive filtering; algorithm weight error vector; convergence; data-adaptive step size; stochastic Newton algorithm; Adaptive filters; Computer errors; Convergence; Equations; Filtering algorithms; Least squares approximation; Least squares methods; Resonance light scattering; Signal processing algorithms; Stochastic processes;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
