Brain learning simulated via electronic replica memory (Vol. 46 No. 4)

A new study shows how a new way of controlling electronic systems endowed with a memory can provide insights into the way associative memories are formed by mimicking synapses.

Scientists are attempting to mimic the memory and learning functions of neurons found in the human brain. To do so, they investigated the electronic equivalent of the synapse, the bridge, making it possible for neurons to communicate with each other. Specifically, they rely on an electronic circuit simulating neural networks using memory resistors. Such devices, dubbed memristor, are well-suited to the task because they display a resistance, which depends on their past states, thus producing a kind of electronic memory. The authors have developed a novel adaptive-control approach for such neural networks, presented in this study. Potential applications are in pattern recognition as well as fields such as associative memories and associative learning.

H. Zhao, L. Li, H. Peng, J. Kurths, J. Xiao and Y. Yang, Anti-synchronization for stochastic memristor-based neural networks with non-modeled dynamics via adaptive control approach, Eur. Phys. J. B 88, 109 (2015)
[Abstract]