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• W2048267110 abstract "Experimental and theoretical evidence shows that biological system processing behavior has nonlinear and chaotic properties. The ability of emerging various solutions for a problem and the existence of a supervisor to guide this variety to become close to the goal, are the two main properties of a problem solver. In this paper, a chaotic neural network which uses chaotic nodes with the logistic map as activation functions is designed to make the ability of emerging various solutions and an NDRAM is considered as a supervisor to guide these various solutions. The proposed chaotic neural network has better performance in comparison with Hopfield, NDRAM, and L. Zhao et al. ChNN." @default.
• W2048267110 created "2016-06-24" @default.
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• W2048267110 date "2011-10-01" @default.
• W2048267110 modified "2023-09-26" @default.
• W2048267110 title "Design of a chaotic neural network for training and retrieval of grayscale and binary patterns" @default.
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• W2048267110 doi "https://doi.org/10.1016/j.neucom.2011.03.037" @default.
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