Hopfield network

A Hopfield network is a type of artificial neural network that serves as a model for memory recall. It operates like a system of interconnected neurons that can store patterns. When it receives a partial or noisy input, it "retrieves" the closest complete pattern from its memory. This is achieved through a process of convergence, where the network adjusts its internal states until it stabilizes at a recognizable memory. Hopfield networks are useful for solving optimization problems and serve as a foundational concept in understanding how information can be stored and recalled in neural-like systems.