Nonlinear least square optimization through parameter estimation using the Unscented Kalman Filter

Versione 1.0.0.0 (2,37 KB) da Yi Cao
A function using the unscented Kalman filter to perform nonlinear least square nonlinear optimizatio
4.8
(4)
10,3K download
Aggiornato 4 feb 2008

Visualizza la licenza

The Kalman filter can be interpreted as a feedback approach to minimize the least equare error. It can be applied to solve a nonlinear least square optimization problem. This function provides a way using the unscented Kalman filter to solve nonlinear least square optimization problems. Three examples are included: a general optimization problem, a problem to solve a set of nonlinear equations represented by a neural network model and a neural network training problem.

This function needs the unscented Kalman filter function, which can be download from the following link:
http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=18217&objectType=FILE

Cita come

Yi Cao (2024). Nonlinear least square optimization through parameter estimation using the Unscented Kalman Filter (https://www.mathworks.com/matlabcentral/fileexchange/18356-nonlinear-least-square-optimization-through-parameter-estimation-using-the-unscented-kalman-filter), MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2007a
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versione Pubblicato Note della release
1.0.0.0

update description