https://doi.org/10.1140/epjs/s11734-025-01654-4
Regular Article
Emotional changes induced by associative memory
1
School of Information Science and Engineering, Dalian Polytechnic University, 116034, Dalian, China
2
School of Faculty of Computing and Information Technology, King Abdulaziz University, 21589, Jeddah, Saudi Arabia
Received:
14
February
2025
Accepted:
24
April
2025
Published online:
5
May
2025
Associative memory and Hopfield neural networks are an important area where artificial intelligence and neuroscience are intertwined, and the core idea is to study the mechanisms of information storage and retrieval in the human brain. In this paper, two memristors are introduced into a three-dimensional Hopfield neural network as electronic synapses to simulate the associative memory function of the hippocampus in the human brain. To begin with, the rationality of the two memristors' designs is verified. Next, the effect on emotion produced when the synaptic weights are changed is investigated using numerical analysis. The firing pattern of Hopfield neural networks was also investigated. The changes made by different emotional states in response to the same associative memory stimulus are also analyzed. Finally, the DSP platform verifies the feasibility of the MATLAB simulation results. This paper provides a theoretical basis for the emotional design of intelligent robots.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
