4.6 Article

Short term memory in input-driven linear dynamical systems

期刊

NEUROCOMPUTING
卷 112, 期 -, 页码 58-63

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2012.12.041

关键词

Short term memory capacity; Fisher memory curve; Recurrent neural network; Echo state network; Reservoir computing

资金

  1. Biotechnology and Biological Sciences Research Council [BB/H012508/1] Funding Source: researchfish
  2. BBSRC [BB/H012508/1] Funding Source: UKRI

向作者/读者索取更多资源

We investigate the relation between two quantitative measures characterizing short term memory in input driven dynamical systems, namely the short term memory capacity (MC) [3] and the Fisher memory curve (FMC) [2]. We show that even though MC and FMC map the memory structure of the system under investigation from two quite different perspectives, for linear input driven dynamical systems they are in fact closely related. In particular, under some assumptions, the two quantities can be interpreted as squared 'Mahalanobis' norms of images of the input vector under the system's dynamics. We also offer a detailed rigorous analysis of the relation between MC and FMC in cases of symmetric and cyclic dynamic couplings. (C) 2013 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据