期刊
JOURNAL OF PHYSICS D-APPLIED PHYSICS
卷 51, 期 28, 页码 -出版社
IOP PUBLISHING LTD
DOI: 10.1088/1361-6463/aac98f
关键词
organic memristors; perceptron; artificial neuronal networks; classification
资金
- Autonomous Province of Trento, Italy (PAT): Developing and studying novel intelligent nano materials and devices towards adaptive electronics and neuroscience applications-MaDEleNA Project
One of the most challenging tasks in neuromorphic applications, in the field of artificial intelligence, is the hardware realization of artificial neural networks (ANNs) which are able to learn during information processing (pattern recognition and classification, approximation, prediction, etc). In this scenario, thanks to their ability to keep the memory of their previous conductive state, memristors are widely considered as promising elements for the efficient implementation of ANNs. In this paper we present a short review of the design and the hardware realization of single and double layer ANNs, which are able to perform linearly separable and non-separable logic classification, using organic memristive devices as elements, ensuring the network weight adjustment.
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