Abstract
The Hamming associative memory hardware realization based on the use of a crossbar with binary memristors (binary resistors with memory) and CMOS circuitry is proposed. It is shown that the binary memristors crossbar realizes the Hamming network first layer properties according to which the first layer neuron output signal is non-negative. This signal is maximal for a neuron with the reference vector closest to the input vector. For a given reference vector dimension, the relationship between the maximum and minimum binary memristors resistances is obtained. It guarantees the Hamming network first layer correct operation. The simulation in the LTSPICE system of the proposed Hamming memory scheme confirmed its operability.
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Tarkov, M.S. (2018). Crossbar-Based Hamming Associative Memory with Binary Memristors. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_44
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DOI: https://doi.org/10.1007/978-3-319-92537-0_44
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