Analysis of Hopfield Model as Associative Memory

Autor:	Silvestri, Matteo
Rok vydání:	2024
Předmět:	Condensed Matter - Disordered Systems and Neural Networks Computer Science - Artificial Intelligence Computer Science - Information Retrieval
Druh dokumentu:	Working Paper
Popis:	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. Comment: 35 pages, 23 figures, 3 codes
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.04264 Zobrazit plný text záznamu View this record from Arxiv