Hi, I'm learning about neural networks from the book "C++ Neural Networks and Fuzzy Logic by Valluru B. Rao". Anyway there was an example to program a hopefield network with 4 neurons. I thought I would program one to make sure i had a good understanding of the example. And when I made it I stored the weights in a 4 by 4 matrix. And then later on the author writes actually writes a program on the same example but instead of storing the weights in a matrix he makes a neuron class that stores 4 connections(including one to itself which is 0). So basically I was wondering what people usually do, do you store the weights in a matrix or inidvidually in a Neuron class? Thanks btw, if anyone's read this book, I think the author's c++ coding style is atrocious!

I prefer to have an actual Neuron class which stores weights of inputs. something like this is appropriate:

class Connection {public:   float weight;   Neuron * source;};class Neuron {private:   std::vector<Connection> inputs;   bool fireState;public:   Neuron(std::vector<Connection> &);   bool getState();   void processInput();   void addInput(Neuron *, float);   void dropInput(Neuron *);   void adjustWeight(Neuron *, float);};

actually I guess that makes alot more sense then just storing the weights in a matrix, because later on when I'm going to be doing feedforward etc networks, it isn't as simple as the hopfield network.

thx

In reply to the AP:
That is exactly why using a Neuron class is such a good idea. If you have reason to prefer grid-matrix later on, you can store matrices in a static matrix member of the class, and just rewrite the accesors to use the matrix, so none of the code actually using the Neurons needs to change.

All of these questions really boil down to what you want to get out of your neural network. Do you want it to be re-usable? Is performance important? Are you looking to solve a specific problem or just write a generic neural network library?

Some designs will be great for one set of needs but poor for another set of needs.

I guess right now Im just writing pretty much generic ANN's. So i may just go with the weights stored in the neuron class for now