Steady State Mean Square Analysis of Standard Maximum Versoria Criterion Based Adaptive Algorithm
S. Radhika, Felix Albu, A. Chandrasekar
Abstract
The Maximum Versoria Criterion (MVC) based adaptive algorithm has recently gained the attention of researchers because of its robustness against impulsive interference and reduced complexity. In this brief, the steady-state Excess Mean Square Error (EMSE) analysis of the standard MVC algorithm is done using the energy conservation relation. For the Gaussian noise case, quadratic equation that can provide the exact value of theoretical steady state EMSE is obtained without any assumptions other than the conventional ones and the Price's theorem. For the non-Gaussian case, an approximate solution using Taylor's expansion is derived. Experimental results validate the obtained theoretical findings.
Topics & Concepts
MathematicsQuadratic equationRobustness (evolution)GaussianAlgorithmStandard deviationApplied mathematicsMean squared errorSteady state (chemistry)Mathematical optimizationStatisticsBiochemistryGeneChemistryGeometryPhysicsPhysical chemistryQuantum mechanicsAdvanced Adaptive Filtering TechniquesBlind Source Separation TechniquesSpeech and Audio Processing