On information characteristics of sparsely encoded binary auto-associative memory

A. Frolov, D. Rachkovskij, D. Húsek
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引用次数: 4

Abstract

A sparsely encoded Willshaw-like attractor neural network based on binary Hebbian synapses is investigated analytically and by computer simulations. A special inhibition mechanism which supports a constant number of active neurons at each time step is used. Informational capacity and size of attraction basins are evaluated for the single-step and the Gibson-Robinson approximations, as well as for experimental results.
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稀疏编码二进制自联想存储器的信息特性研究
本文研究了一种基于二进制Hebbian突触的稀疏编码类威尔肖吸引子神经网络。采用一种特殊的抑制机制,在每个时间步长支持恒定数量的活动神经元。对单步法和Gibson-Robinson近似法以及实验结果进行了信息容量和大小的评价。
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