Filtering-Based Accelerated Estimation Approach for Generalized Time-Varying Systems With Disturbances and Colored Noises
Yan Ji, Anning Jiang
Abstract
This brief studies the parameter estimation problem of a generalized time-varying system by using a novel gradient descent algorithm. The time-varying parameters are estimated by the accelerating gradient descent algorithm under considering the measurable disturbance factors. The proposed algorithm increases the convergence rate by adding a momentum term to the correction of the parameter updated estimates. In addition, a data filter is introduced to filter the input and output data, so as to eliminate the interference of colored noise to the accuracy of parameter estimation. A numerical example shows the effectiveness of the proposed algorithm.
Topics & Concepts
Gradient descentConvergence (economics)Control theory (sociology)Filter (signal processing)AlgorithmEstimation theoryTerm (time)Noise (video)Colors of noiseColoredStochastic gradient descentRate of convergenceMathematicsComputer scienceMomentum (technical analysis)Artificial neural networkControl (management)Artificial intelligenceImage (mathematics)Materials scienceEconomic growthFinanceChannel (broadcasting)Composite materialComputer visionComputer networkPhysicsEconomicsQuantum mechanicsControl Systems and IdentificationStructural Health Monitoring TechniquesAdvanced Adaptive Filtering Techniques