Yamaguti Yutaka, Tsuda Ichiro
Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka 811-0295, Japan.
Chubu University Academy of Emerging Sciences, Chubu University, Kasugai, Aichi 487-8501, Japan.
Chaos. 2021 Jan;31(1):013137. doi: 10.1063/5.0019116.
We propose an extended reservoir computer that shows the functional differentiation of neurons. The reservoir computer is developed to enable changing of the internal reservoir using evolutionary dynamics, and we call it an evolutionary reservoir computer. To develop neuronal units to show specificity, depending on the input information, the internal dynamics should be controlled to produce contracting dynamics after expanding dynamics. Expanding dynamics magnifies the difference of input information, while contracting dynamics contributes to forming clusters of input information, thereby producing multiple attractors. The simultaneous appearance of both dynamics indicates the existence of chaos. In contrast, the sequential appearance of these dynamics during finite time intervals may induce functional differentiations. In this paper, we show how specific neuronal units are yielded in the evolutionary reservoir computer.
我们提出了一种能展示神经元功能分化的扩展型回声状态网络。回声状态网络通过进化动力学来实现内部状态的改变，我们将其称为进化回声状态网络。为了使神经元单元根据输入信息表现出特异性，需要控制内部动力学，使其在扩张动力学之后产生收缩动力学。扩张动力学放大输入信息的差异，而收缩动力学有助于形成输入信息的簇，从而产生多个吸引子。这两种动力学的同时出现表明存在混沌。相比之下，在有限时间间隔内这些动力学的相继出现可能会诱导功能分化。在本文中，我们展示了在进化回声状态网络中如何产生特定的神经元单元。
