Transient Theoretical Analysis of Diffusion RLS Algorithm for Cyclostationary Colored Inputs
Wei Gao, Jie Chen, Cedric Richard
Abstract
Convergence of the diffusion RLS (DRLS) algorithm to steady-state has been extensively studied in the literature, whereas no analysis of its transient convergence behavior has been reported yet. In this letter, we conduct a theoretical analysis of the transient behavior of the DRLS algorithm for cyclostationary colored inputs, in the mean and mean-square error sense. The resulting analytical models allows us to thoroughly investigate the convergence behavior of the algorithm over adaptive networks in such complex scenarios. Simulation results support the accuracy and correctness of the theoretical findings.
Topics & Concepts
Convergence (economics)CorrectnessCyclostationary processTransient (computer programming)AlgorithmComputer scienceColoredTransient analysisAdaptive algorithmDiffusionAlgorithm designMathematicsPosition (finance)Term (time)Adaptive filterSignal processingColors of noiseTransient responseControl theory (sociology)Adaptive systemNoise (video)Error analysisStochastic processDiffusion equationComputational complexity theoryApplied mathematicsMean squared prediction errorRecursive least squares filterSpectral analysisAdvanced Adaptive Filtering TechniquesBlind Source Separation TechniquesSpeech and Audio Processing