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What is Overview of Hopfield Networks about?

Hopfield networks consist of recurrently connected binary threshold units. John Hopfield showed that if the connections are symmetric, the network will settle into a minimum energy state, allowing it to act as an associative memory. The network can retrieve incomplete or corrupted patterns by settling into the closest stored memory. A Hopfield network is fully connected, with symmetric weights between nodes updated using Hebbian learning. The network is run asynchronously or synchronously until reaching a s

Author

Bhuvneshwar Sharma (Bhuvi)

Language

EN