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• W1520453958 abstract "Two types of novel cellular neural networks based on mem-elements are proposed, namely, MC-CNN and EM-CNN. The MC-CNN lets a memcapacitor replace the conventional linear capacitor of a cellular neural network cell. This improvement takes advantage of the nanoscale of memcapacitor and its natural nonlinearity, which makes the MC-CNN more compact and the output function simplified. Mathematical analysis of stability and simulation of image processing is presented to verify the feasibility and performance of MC-CNN. The EM-CNN is an economical improvement of the memristor synapse cellular neural network. In the EM-CNN, based on the symmetry of CNN templates, the amount of memristors and voltage-controlled current source is largely reduced. Thus, the EM-CNN is not only economical on the fabricating cost of CNN but also possesses a simpler cell structure which is beneficial to better implementation of CNN." @default.
• W1520453958 created "2016-06-24" @default.
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• W1520453958 date "2015-07-01" @default.
• W1520453958 modified "2023-09-27" @default.
• W1520453958 title "Two novel cellular neural networks based on mem-elements" @default.
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• W1520453958 doi "https://doi.org/10.1109/chicc.2015.7260171" @default.
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