The Research of Fault Tolerance of Memristor-Based Artificial Neural Networks

Abstract

A general approach to the development of memristor-based artificial neural networks (ANNM) operated with specified fault tolerance (FT) is formulated and applied in the paper. It is shown that ensuring the required ANNM FT is related to ensuring the required accuracy of their operation at all the structural and functional hierarchy levels. The paper proposes a quantitative FT criterion that can be used to create ANNM reliability block diagrams, calculate and optimize reliability in accord with the actual Russian and international standards. The application of the proposed algorithm is considered on the example of the ANN performing an approximation of mathematical functions, the synapses of which are implemented with memristors. It is found that a potentially high ANNM FT cannot be achieved by itself only because of the massive parallelism of artificial neural networks. Instead it depends on many factors and requires the application of special physical and information technologies at all the ANNM life cycle stages.