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This paper proposes the diffusion circuit for Autonomous Ratio-Memory Cellular Nonlinear Networks (ARMCNNs). ARMCNNs can tolerate large variations of ratio weights which has been shown in our previous paper. However, in our previous circuit implementation, the synapse weight circuit between neighboring neurons was composed of two voltage to current converters (V/Is) and current mirrors. The layout...
The stability analysis via the Lyapunov theorem for Autonomous Ratio-Memory Cellular Nonlinear Networks (ARMCNNs) is proposed. A conservative domain of attraction (DOA) is found from the stability analysis through a graphical method without complicated numerical analysis. The stability analysis shows that ARMCNNs can tolerate large ratio weight variations. This paper also presents the ARMCNN with...
A new type of CNN associative memory called the autonomous ratio-memory cellular nonlinear network (ARMCNN) is proposed and analyzed. In the proposed ARMCNN, the input noisy patterns are sent into the cells as the initial cell state voltages. The proposed ARMCNN has the advantages of higher recognition rate (RR), higher number of learned and recognized patterns, and smaller signal ranges of cell state...
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