Java Hopfield Neural Network

The Hopfield neural network was developed by Dr. John Hopfield in 1979. The Hopfield network is a single layer recurrent neural network. The Hopfield network always maintains a "current state" which is the current output of the neural network. The Hopfield neural network also has a energy property, which is calculated exactly the same as the temperature property of the Boltzmann machine. The Hopfield network is trained for several patterns. The state of the Hopfield network will move towards the closest patter, thus "recognizing" that pattern. As the Hopfield network moves towards one of these patterns, the energy lowers.

Neural Networks and Physical Systems with Emergent Collective Computational Abilities
Proceedings of the National Academy of Sciences, 79, pp. 2554-2558, 1982

The Hopfield Neural Network modeled in the Encog Workbench looks like this: