Hopfield networks

A Hopfield network is a totally connected neural network often used as autoencoder. Like Boltzmann machine, the Hopfield network is related to {[spin glass models}} in physics. Hopfield networks differ from Boltzmann machines principally in the update model for node weights, notably, while Hopfield networks adopt a continuous learning mechanism with smooth thresholds, similar to that in backpropogation; Boltzmann machine use stochastic firing that effectively creates a Markov process, and are more similar to spiking neural networks.

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