4.7

4.7 | 11 ratings Rate this file 66 Downloads (last 30 days) File Size: 2.18 KB File ID: #18289

Neural Network training using the Extended Kalman Filter

by

 

10 Jan 2008 (Updated )

A function using the extended Kalman filter to train MLP neural networks

| Watch this File

File Information
Description

The extended Kalman filter can not only estimate states of nonlinear dynamic systems from noisy measurements but also can be used to estimate parameters of a nonlinear system. A direct application of parameter estimation is to train artificial neural networks. This function and an embeded example shows a way how this can be done.

Acknowledgements

Learning The Extended Kalman Filter inspired this file.

This file inspired Neural Network Training Using The Unscented Kalman Filter.

MATLAB release MATLAB 7.5 (R2007b)
Other requirements It requires the ekf function, which can be downloaded from the following link: http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=18189&objectType=FILE
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Comments and Ratings (13)
11 Jun 2013 SaiNave

I have suffered this kind of error using this file

Maximum recursion limit of 500 reached. Use set(0,'RecursionLimit',N) to change the
limit. Be aware that exceeding your available stack space can crash MATLAB and/or your
computer.

Error in nnekf

03 Jan 2013 Kalyan

good

17 Jun 2012 luo

good jod

17 Jun 2012 luo

good

05 Jun 2012 Daniel

For newer versions of matlab, it's recommended to use:

rng('default')
rng('shuffle')

instead of:

rand('state', 0)

29 Dec 2011 Dinie Muhammad

Great job!

05 Apr 2009 V. Poor  
08 Oct 2008 x y

Great job!

16 Sep 2008 Devanathan M

Very nice

28 Jul 2008 piyush singhal

it is a good effort pl generate codes for it which can be help ful for mpc

21 Jul 2008 a s  
21 Feb 2008 lekouch khalid

is an intersent work

21 Feb 2008 mahendra shukla

too good

Contact us