Exact expectation analysis of the sign-data LMS algorithm for i.i.d. input data

• Published in: [1992] Conference Record of the Twenty-Sixth Asilomar Conference on Signals, Systems & Computers pp. 566 - 570 vol.1
• Main Author: Douglas, S.C.
• Format: Conference Proceeding
• Language: English
• Published: IEEE Comput. Soc. Press 1992
• Subjects: Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Convergence; Filtering algorithms; Hardware; Least squares approximation; Noise generators; Nonlinear equations; Stochastic processes
• ISBN: 0818631600; 9780818631603
• ISSN: 1058-6393
• DOI: 10.1109/ACSSC.1992.269208

The author presents an automated method of deriving an exact description of the convergence behavior of a class of nonlinearity modified data adaptive algorithms for system identification modeling with independent, identically distributed (i.i.d.) samples as input data. Using the method, a set of linear equations that exactly describes a nonlinear data algorithm's stochastic behavior at each time step is identified. Moreover, precise bounds upon the step size to guarantee convergence of the algorithm in the mean and in mean square are obtained. Simulations indicate that the equations produced by the exact method are much more accurate than previous analyses in predicting convergence behavior of the sign-data LMS adaptive algorithm particularly in fast adaptation situations.< >