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Memristive Perceptron for Combinational Logic Classification

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  • Lidan Wang
  • Meitao Duan
  • Shukai Duan

Abstract

The resistance of the memristor depends upon the past history of the input current or voltage; so it can function as synapse in neural networks. In this paper, a novel perceptron combined with the memristor is proposed to implement the combinational logic classification. The relationship between the memristive conductance change and the synapse weight update is deduced, and the memristive perceptron model and its synaptic weight update rule are explored. The feasibility of the novel memristive perceptron for implementing the combinational logic classification (NAND, NOR, XOR, and NXOR) is confirmed by MATLAB simulation.

Suggested Citation

  • Lidan Wang & Meitao Duan & Shukai Duan, 2013. "Memristive Perceptron for Combinational Logic Classification," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, May.
    • Handle: RePEc:hin:jnlmpe:625790
    DOI: 10.1155/2013/625790
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