Jan 10, 2017 · Then we present a novel heuristic particle swarm search algorithm called sliding mode controlling particle swarm optimization (SMCPSO) algorithm ...
In order to estimate the parameters of linear dynamic systems more effectively, we tend to develop a heuristic particle swarm search algorithm to solve the ...
Maximum likelihood parameter estimation of dynamic systems by heuristic swarm search ... estimation with sensor position perturbation using particle swarm ...
Maximum likelihood parameter estimation of dynamic systems by heuristic swarm search. As a method of estimating the parameters of statistical models in ...
Adaptation algorithms have been mathematically derived following different methods of adaptation which include Maximum Likelihood Estimation (MLE), Covariance ...
Maximum likelihood parameter estimation of dynamic systems by heuristic swarm search. Citing Article. January 2017. Intelligent Data Analysis. Yongzhong Lu.
Here we present a method for the robust estimation of system parameters based on the censoring of data and employing the maximum likelihood estimation. Several ...
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The objective of DOPS is to obtain near optimal parameter estimates for large biochemical models within a relatively few function evaluations. DOPS uses multi- ...
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Jul 29, 2020 · In this research we aim to infer both the structure and parameters of a dynamic system simultaneously by particle swarm optimization (PSO)
This paper introduces a maximum-likelihood method for the nonparametric estimation of smooth spectra from irregularly sampled observations, ...