  This paper continues on the work of the B-Matrix approach in hebbian learning
proposed by Dr. Kak. It reports the results on methods of improving the memory
retrieval capacity of the hebbian neural network which implements the B-Matrix
approach. Previously, the approach to retrieving the memories from the network
was to clamp all the individual neurons separately and verify the integrity of
these memories. Here we present a network with the capability to identify the
"active sites" in the network during the training phase and use these "active
sites" to generate the memories retrieved from these neurons. Three methods are
proposed for obtaining the update order of the network from the proximity
matrix when multiple neurons are to be clamped. We then present a comparison
between the new methods to the classical case and also among the methods
themselves.
