A current-mode cellular neural network implementation

A compact and efficient current-mode circuit implementation for a cellular neural network is presented. The implementation presented consists of current amplifiers, simple current mirrors, simple current sources, and transconductors. Experimental results from first-generation CMOS monolithic prototypes with fixed connection weights show the feasibility of the proposed implementation by successfully performing edge detection and noise removal image processing. >

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