My objective is to train a NN to recognize handwritten digits (Black/White bit pattern). The neural net seems to expect each input (training/test instance) as a column in a matrix/cell.
I do not wish for a full connection between the input and the immediate NN layer. I want to specify a more localized mapping between the input bits and the hidden neurons. In essence a mapping best descried if both the layer and the input can treated as 2 dimensional.
When my training instances are specified as columns, they loose a part of adjacency information.
How can I feed the NN an 2-D input?
I've crawled through much of the tutorial style documentation and couldn't find much that helped. Being rather new to matlab, it's a bit overwhelming. Links to relevant documentation are also welcome.
Also, what more information would be useful to answer this question?