"Prateek " <firstname.lastname@example.org> wrote in message news:email@example.com... > I have been trying to make a Hopfield Network to store the data i have > which is a matrix of dimension 26X10000 but with no success following is > the code i am writing and the errors which i am getting please help me out >>> net=newhop(mat') > ??? Out of memory. Type HELP MEMORY for your options.
"newhop(T) takes an RxQ matrix of Q target vectors T with element values of +1 or -1, and returns a new Hopfield recurrent neural network with stable points at the vectors in T."
So R is 10000 and Q is 26 in this case (since you transposed mat when you called NEWHOP.) You're trying to take 26 10000-dimension vectors and generate a network from them? Seems to me you have MUCH too small a data set to be able to draw any sort of conclusions.
Do you instead want to operate on 10000 26-dimension vectors? That's probably going to give you a better chance of success, though I'd guess you'd do better with more data. If so, don't transpose.