Guiding principle of reservoir computing based on "small-world" network.

ABSTRACT: Reservoir computing is a computational framework of recurrent neural networks and is gaining attentions because of its drastically simplified training process. For a given task to solve, however, the methodology has not yet been established how to construct an optimal reservoir. While, "small-world" network has been known to represent networks in real-world such as biological systems and social community. This network is categorized amongst those that are completely regular and totally disordered, and it is characterized by highly-clustered nodes with a short path length. This study aims at providing a guiding principle of systematic synthesis of desired reservoirs by taking advantage of controllable parameters of the small-world network. We will validate the methodology using two differen

SUBMITTER: Kitayama KI 

PROVIDER: S-EPMC9537422 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature