Abstract
A double-pattern associative memory neural network with “pattern loop” is proposed. It can store 2N bit bipolar binary patterns up to the order of 22N, retrieve part or all of the stored patterns which all have the minimum Hamming distance with input pattern, completely eliminate spurious patterns, and has higher storing efficiency and reliability than conventional associative memory. The length of a pattern stored in this associative memory can be easily extended from 2N to kN.
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References
J. J. Hopfield, Neural networks and physical systems with emergent collective computational abilities, Proceedings National Academy of Sciences, Vol. 79, No. 8, pp. 2554–2558,1982.
J B. Kosko, Hetero-associative memories, IEEE Trans. on Systems, Man and Cybernetics, Vol. 18, No. 1, pp. 49–60,1988.
T. D. Chiueh, R. M. Goodman, Recurrent correlation associative memories, IEEE Trans. on Neural Networks, Vol. 2, No. 2, pp. 275–284, 1991.
J. Wang, Z. Y. Mao, A new associative memory neural network using loop as storage unit, Computer Engineering and Applications, Vol. 39, No. 4, pp. 26–29,2003.
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Wang, J., Mao, Z. Double-pattern associative memory neural network with pattern loop. J. Control Theory Appl. 2, 193–195 (2004). https://doi.org/10.1007/s11768-004-0068-9
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DOI: https://doi.org/10.1007/s11768-004-0068-9