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Hopfield network

   Also found in: Wikipedia 0.01 sec.
(artificial intelligence)Hopfield network - (Or "Hopfield model") A kind of neural network investigated by John Hopfield in the early 1980s. The Hopfield network has no special input or output neurons (see McCulloch-Pitts), but all are both input and output, and all are connected to all others in both directions (with equal weights in the two directions). Input is applied simultaneously to all neurons which then output to each other and the process continues until a stable state is reached, which represents the network output.


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Some specific areas examined include virtual reality simulation and analysis of handling stability for forest fire patrolling vehicles, experimental research on multimedia teaching for sports aerobics, a clustering algorithm in wireless networks, and a license plate recognition system based on an orthometric Hopfield network.
In the Hopfield network all the neurons are connected to one another; if we label every node as [x.
Later, in the associate memory discussion, the reader trips over Hopfield networks and Hebb's rule.
 
 
 
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