Experimental demonstration of associative memory with memristive neural networks
Yuriy V. Pershin, Massimiliano Di Ventra

TL;DR
This paper demonstrates an electronic neural network using memristors to emulate synapses, successfully creating associative memory, which advances the development of adaptive and learning-capable artificial neural systems.
Contribution
It introduces a memristor emulator that replicates synaptic behavior and experimentally demonstrates associative memory in a simple electronic neural network.
Findings
Successful formation of associative memory in a neural network
Memristor emulator replicates key synaptic properties
Potential for complex learning and adaptive behaviors
Abstract
When someone mentions the name of a known person we immediately recall her face and possibly many other traits. This is because we possess the so-called associative memory, that is the ability to correlate different memories to the same fact or event. Associative memory is such a fundamental and encompassing human ability (and not just human) that the network of neurons in our brain must perform it quite easily. The question is then whether electronic neural networks (electronic schemes that act somewhat similarly to human brains) can be built to perform this type of function. Although the field of neural networks has developed for many years, a key element, namely the synapses between adjacent neurons, has been lacking a satisfactory electronic representation. The reason for this is that a passive circuit element able to reproduce the synapse behaviour needs to remember its past…
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Neural dynamics and brain function · Photoreceptor and optogenetics research
