Unconstrained Optimization using the Extended Kalman Filter

Version 1.0.0.0 (2.08 KB) by Yi Cao
A function using the extended Kalman filter to perform unconstrained nonlinear optimization
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Updated 4 Feb 2008

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The Kalman filter is actually a feedback approach to minimize the estimation error in terms of sum of square. This approach can be applied to general nonlinear optimization. This function shows a way using the extended Kalman filter to solve some unconstrained nonlinear optimization problems. Two examples are included: a general optimization problem and a problem to solve a set of nonlinear equations represented by a neural network model.

This function needs the extended Kalman filter function, which can be download from the following link:
http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=18189&objectType=FILE

Cite As

Yi Cao (2024). Unconstrained Optimization using the Extended Kalman Filter (https://www.mathworks.com/matlabcentral/fileexchange/18286-unconstrained-optimization-using-the-extended-kalman-filter), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2007b
Compatible with any release
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Version Published Release Notes
1.0.0.0

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