A new mixed-signal feed-forward neural network with on-chip learning
Mitra Mirhassani, Majid Ahmadi, William Cameron Miller · 2005
A new mixed-signal feed-forward neural network for pattern/shape recognition problems is proposed. The network has a mixed-signal structure, operations are performed in analog and weights are stored in digital. To increase the network robustness, on-chip training with Madaline Rule III is used. The proposed architecture uses time-multiplexing to increase the network density and resistive-type neurons for their self-scaling property. The results of an XOR network are presented to test the network.