I was hoping for more progress, but I did not put in the work required. Over the holidays I’ve been mostly lazy. But anyway, I did manage to have the inhibitory neurons working. The project is very small and may seem even smaller to the untrained eye 🙂 I worked on a 2 by 2 matrix, with only 2 layers, one layer to receive the pattern the other layer to show the output. Second layer is what I call a compression layer since it’s doing a data reduction more or less like a complex cell would, a single cell responds to similar pattern such as a vertical lines .
Why is this important at all ? Because otherwise a pattern eventually will spread all over the network in obscure ways. Say you have a pattern for letter A… some layers down the line you may find that pattern stored as an AAAAAAA chain without an inhibitory effect.
How important is this in the bigger picture ? Not nearly enough, but now I can move onto the next big issue, make the network learn based on feed-back… What does that mean ? it means that now I should have a 3rd layer which should associate 2 unrelated patterns as being the same, based on my feed-back.. take the two pattern above, a vertical line and a horizontal line. A third layer should have a single neuron firing whether the vertical line is showing or the horizontal one is… because I say so, you see 😀
When ? God knows 🙂