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Synapse based on two successive memristors builds the synaptic weights of the artificial neural network for training three-bit parity problem and five-character recognition. Methods: The proposed memristor synapse circuit creates positive weights in the range [0;1], and maps it to range [-1;1] to program both the positive and negative weights. The proposed scheme achieves the same accuracy rate as the conventional bridge synapse schemes which consist of four memristors. Results and Conclusion: However, proposed synapse circuit decreases 50% the number of memristors and 76.88% power consumption compared to the conventional bridge memristor synapse.

Multilayer Neural Network with Synapse Based on Two Successive Memristors