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Neural Network training using the Extended Kalman Filter

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

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13 Ratings

33 Downloads

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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.

Comments and Ratings (19)

Ahmad Alias

can i get the nnekf with load of data.

Andreas D

Unfortunately i am getting the following error:

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 datenum

How can i fix it? Thank you!

feras

feras (view profile)

Anitha

Anitha (view profile)

if the size of x and y is different.,what change should be done in the code

Deep Gogoi

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 ==> datenum

Deep Gogoi

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 ==> datenum

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

Kalyan

Kalyan (view profile)

good

luo

luo (view profile)

good jod

luo

luo (view profile)

good

Daniel

Daniel (view profile)

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

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

instead of:

rand('state', 0)

Great job!

V. Poor

x y

Great job!

Devanathan M

Very nice

piyush singhal

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

a s

lekouch khalid

is an intersent work

mahendra shukla

too good

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