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RECURRENT NEURAL NETWORK
Hopfield nets; Hopfield model; Hopfield neural network; Hopfield networks; Hopfield net; Hopfield Network; Training Hopfield networks
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Hopfield network
<artificial intelligence> (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.
(1997-10-11)
Hopfield network
A Hopfield network (or Ising model of a neural network or Ising–Lenz–Little model) is a form of recurrent artificial neural network and a type of spin glass system popularised by John Hopfield in 1982 as described earlier by Little in 1974 based on Ernst Ising's work with Wilhelm Lenz on the Ising model. Hopfield networks serve as content-addressable ("associative") memory systems with binary threshold nodes, or with continuous variables.
Hopfield model
ويكيبيديا
Hopfield network
A Hopfield network (or Ising model of a neural network or Ising–Lenz–Little model) is a form of recurrent artificial neural network and a type of spin glass system popularised by John Hopfield in 1982 as described by Shun'ichi Amari in 1972 and by Little in 1974 based on Ernst Ising's work with Wilhelm Lenz on the Ising model. Hopfield networks serve as content-addressable ("associative") memory systems with binary threshold nodes, or with continuous variables. Hopfield networks also provide a model for understanding human memory.
