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
인용 양식
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. 검색됨 .
MATLAB 릴리스 호환 정보
플랫폼 호환성
Windows macOS Linux카테고리
- Signal Processing > Signal Processing Toolbox > Digital and Analog Filters > Digital Filter Design > Adaptive Filters >
태그
도움
받음: Learning the Extended Kalman Filter
줌: Nonlinear least square optimization through parameter estimation using the Unscented Kalman Filter
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!버전 | 게시됨 | 릴리스 정보 | |
---|---|---|---|
1.0.0.0 | update description |