Neural Network Toolbox

Architecture

The architecture of the network that we are using follows.

As noted, the input p to this network merely supplies the initial conditions.

The Hopfield network uses the saturated linear transfer function satlins.

For inputs less than -1 satlins produces -1. For inputs in the range -1 to +1 it simply returns the input value. For inputs greater than +1 it produces +1.

This network can be tested with one or more input vectors which are presented as initial conditions to the network. After the initial conditions are given, the network produces an output which is then fed back to become the input. This process is repeated over and over until the output stabilizes. Hopefully, each output vector eventually converges to one of the design equilibrium point vectors that is closest to the input that provoked it.

Hopfield Network

Design (newhop)

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