School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710119, China.
Phys Rev E. 2017 Jan;95(1-1):012309. doi: 10.1103/PhysRevE.95.012309. Epub 2017 Jan 12.
We study the stability of patterns in Hopfield networks in which a part of memorized patterns are similar. The similarity between patterns impacts the stability of these patterns, but the stability of other independent patterns is only changed slightly. We show that the stability of patterns is affected in different ways by similarity. For networks storing a number of patterns, the similarity between patterns enhances the pattern stability. However, the stability of patterns can be weakened by the similarity when networks store fewer patterns, and the relation between the stability of patterns and similarity is nonmonotonic. We present a theoretical explanation of the effect of similarity on stability using signal-to-noise-ratio analysis.
我们研究了记忆模式中有部分相似的 Hopfield 网络中模式的稳定性。模式之间的相似性会影响这些模式的稳定性,但其他独立模式的稳定性只会略有改变。我们表明,相似性以不同的方式影响模式的稳定性。对于存储多个模式的网络,模式之间的相似性会增强模式的稳定性。然而,当网络存储较少的模式时,模式的相似性会削弱其稳定性,并且模式稳定性与相似性之间的关系是非单调的。我们使用信噪比分析方法对相似性对稳定性的影响提出了理论解释。