A Spiking Neural Network Based on Thalamo–Cortical Neurons for Self–Learning Agent Applications

The paper proposes a non-iterative training algorithm for a power efficient SNN classifier for applications in self-learning systems. The approach uses mechanisms of preprocessing of signals from sensory neurons typical of a thalamus in a diencephalon. The algorithm concept is based on a cusp catast...

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發表在:	International Journal of Applied Mathematics and Computer Science
Main Authors:	Huderek Damian, Szczęsny Szymon, Pietrzak Paweł, Rato Raul, Przyborowski Łukasz
格式:	Article
語言:	英语
出版:	Sciendo 2024-09-01
主題:	self-learning systems classification spiking neural networks feature recognition learning by routing
在線閱讀:	https://doi.org/10.61822/amcs-2024-0033