Feedforward Neural Network with Adapt Training
6 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
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?
0 commentaires
Réponse acceptée
Sarah Mohamed
le 4 Jan 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.
Plus de réponses (1)
Greg Heath
le 5 Jan 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
Voir également
Catégories
En savoir plus sur Sequence and Numeric Feature Data Workflows dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!