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Analysis of Hopfield Model as Associative Memory (2402.04264v1)
Published 24 Jan 2024 in cond-mat.dis-nn, cs.AI, and cs.IR
Abstract: This article delves into the Hopfield neural network model, drawing inspiration from biological neural systems. The exploration begins with an overview of the model's foundations, incorporating insights from mechanical statistics to deepen our understanding. Focusing on audio retrieval, the study demonstrates the Hopfield model's associative memory capabilities. Through practical implementation, the network is trained to retrieve different patterns.
- Agliari, E. (2023). Modelli di Reti Neurali. Università degli Studi di Roma La Sapienza.
- Bellina, A. (2021). Modello di Hopfield con Diluizione Sinaptica Simmetrica Casuale. Università degli Studi di Roma La Sapienza.
- Patti, A. (2022). Retrieving mismatched memory patterns in the Hopfield model of neural networks. Università degli Studi di Roma La Sapienza.
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