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Neural Network training using the Extended Kalman Filter


Yi Cao


10 Jan 2008 (Updated )

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

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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.


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
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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

Error in nnekf

Comment only
03 Jan 2013 Kalyan



Comment only
17 Jun 2012 luo


good jod

17 Jun 2012 luo



05 Jun 2012 Daniel


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


instead of:

rand('state', 0)

29 Dec 2011 Dinie Muhammad

Dinie Muhammad

Great job!

05 Apr 2009 V. Poor

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

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