Simple Competitive Learning Networks
In competitive networks, output units compete for the right to respond.
Goal: method of clustering – divide the data into a number of clusters such that the inputs in the same cluster are in some sense similar.
A basic competitive learning network has one layer of input nodes and one layer of output nodes. Binary valued outputs are often (but not always) used. There are as many output nodes as there are classes.
Often (but not always) there are lateral inhibitory connections between the output nodes.(in simulations, the function of the lateral connections can be replaced with a different algorithm)
The output units are also often called grandmother cells. The term grandmother cell comes from discussions as to whether your brain might contain cells that fire only when you encounter your maternal grandmother, or whether such higher level concepts are more distributed.