Feedforward Neural Network with Adapt Training
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I have 1*600 cell array for input and target. Each cell array consists of 960*1 samples. So there are 600 elements with 960*1 samples. I have divided columnwise for training.
But now i am facing Memory Issue(array exceeds maximum array size) for Jacobian calculations. I have a situation where i have to train the network for 960*1 (input) to 960*1 (target) only.
i tried to do using for loop[feed 960*1 at a time] -> configure multiple net ->adapt() incremental training-> cal MSE .
i'm facing following error
--Error using + Matrix dimensions must agree.
Error in nn7.grad2 (line 95) gA{i} = gA{i} + LWderivP' * gLWZ{k,i};
This is the error from matlab predefined function. Can you help me in solving this please?
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Respuesta aceptada
Sarah Mohamed
el 4 de En. de 2018
Take a look at the following post for a similar issue that appears to have been caused by the network configuration:
If this doesn't resolve the issue, it would be helpful if you could post the code that generates the error.
Más respuestas (1)
Greg Heath
el 5 de En. de 2018
Think in terms of column vectors: Each of N I-dimensional "I"nput vectors causes 1 of the N O-dimensional "O"utput vectors. The corresponding data sizes are
[ I N ] = size(Input)
[ O N ] = size(Target) % = size(Output)
Hope this helps.
Thank you for formally accepting my answer
Greg
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