I'm a new at the cellular neural network, which is a special case of the recurrent neural network: my questions are: I understand the implementation of Chua circuit for the CNN, but I still need to
1- understand intuitively why every cell in CNN receives a summation of the outputs from the surrounding cells? mathematically it is clear how to analysis it but I'm talking about the idea behind that. 2- When do we decide to change the elements of matrix A and B or one of them, since some papers they set matrix B to zeros and sometimes matrix A to zero? I know they want to reduce the error but there is something still not clear. 3-I want to use CNN to classify images and I'm looking to a good reference to do that.
Thank you in advance,