Hopfield Network Simulator Investigates how many patterns a network can hold versus the accuracy with which the network can recall
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simulate neural network simulator neural network Hopfield simulator Hopfield investigation Hopfield

Hopfield Network Simulator Description

Investigates how many patterns a network can hold versus the accuracy with which the network can recall Hopfield Network Simulator is an open source simulation which investigates how many patterns a Hopfield Network can hold versus the accuracy with which the network can recall. For example, a network with only 5 neurons simply cannot accurately recall many patterns, and this simulator allows you to investigate this relationship.According to Wikipedia: "A Hopfield net is a form of recurrent artificial neural network invented by John Hopfield. Hopfield nets serve as content-addressable memory systems with binary threshold units. They are guaranteed to converge to a local minimum, but convergence to one of the stored patterns is not guaranteed."There are two PDFs included with the Xcode project, a theoretical overview and a detailed implementation guide. The simulator produces comma separated value (CSV) files, which can be opened in Numbers or Excel for graphing.

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