Publication | Closed Access
The LMS algorithm with delayed coefficient adaptation
335
Citations
7
References
1989
Year
Numerical AnalysisAdaptive FilterNumerical ComputationEngineeringMachine LearningStep SizeCoefficient UpdateLms AlgorithmComputer EngineeringBusinessNumerical StabilityApproximation AlgorithmsAdaptive AlgorithmUpper BoundNumerical MethodsSignal ProcessingAdaptive Optimization
The behavior of the delayed least-mean-square (DLMS) algorithm is studied. It is found that the step size in the coefficient update plays a key role in the convergence and stability of the algorithm. An upper bound for the step size is derived that ensures the stability of the DLMS. The relationship between the step size and the convergence speed, and the effect of the delay on the convergence speed, are also studied. The analytical results are supported by computer simulations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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