Parcourir par sujet "Adaptive filters"
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Adaptive Bayesian Inference Framework for Joint Model and Noise Identification
(2022)Model updating, the process of inferring a model from data, is prone to the adverse effects of modeling error, which is caused by simplification and idealization assumptions in the mathematical models. In this study, an ... -
Adaptive Kalman filters for nonlinear finite element model updating
(2020)This paper presents two adaptive Kalman filters (KFs) for nonlinear model updating where, in addition to nonlinear model parameters, the covariance matrix of measurement noise is estimated recursively in a near online ... -
Nonlinear Model Updating Using Recursive and Batch Bayesian Methods
(2020)This paper studies the performance of recursive and batch Bayesian methods for nonlinear model updating. Unscented Kalman filter (UKF) is selected to represent the recursive Bayesian method, and two UKF approaches are ... -
Tracking differential evolution algorithms: An adaptive approach through multinomial distribution tracking with exponential forgetting
(2012)Several Differential Evolution variants with modified search dynamics have been recently proposed, to improve the performance of the method. This work borrows ideas from adaptive filter theory to develop an "online" ... -
Tracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting
(2012)An active research direction in Particle Swarm Optimization (PSO) is the integration of PSO variants in adaptive, or self-adaptive schemes, in an attempt to aggregate their characteristics and their search dynamics. In ...