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Stochastic Gradient Algorithms with a Gradient-Adaptive and Limited Step-Size
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1994/03/25
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Adaptive Signal Processing
adaptive filter, LMS algorithm, step size, fast convergence, misadjustment, interference, robustness, echo cancellation,
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This paper proposes new algorithms for adaptive FIR filters. The proposed algorithms provide both fast convergence and small final misadjustment with an adaptive step size even under an interference to the error. The basic algorithm pays special attention to the interference which contaminates the error. To enhance robustness to the interference, it imposes a special limit on the increment/decrement of the step-size. The limit itself is also varied according to the step-size. The basic algorithm is extended for application to nonstationary signals. Simulation results with white signals show that the final misadjustment is reduced by up to 22 dB under severe observation noise at a negligible expense of the convergence speed. An echo canceler simulation with a real speech signal exhibits its potential for a nonstationary signal.