Work

Versatile reservoir computing for heterogeneous complex networks

Year: 2025

Type: article

Abstract: Can a small, versatile machine be trained on the time series of a few elements in a large, heterogeneous complex system, and then substitute any element while preserving its collective dynamics over a finite time horizon? Leveraging the technique of reservoir computing (RC) in machine learning, the authors demonstrate that such a machine can indeed be constructed, and performs effectively in general complex networks of heterogeneous dynamics and structure. The all-in-one, plug-and-play nature of versatile RC offers substantial convenience for maintaining the functionality of real-world complex systems that suffer sporadic or temporary component failures.

Source: Physical Review Applied

DOI: 10.1103/vb8m-b151

Authors: Yao Du, Huawei Fan, Xingang Wang

Institutions: Shaanxi Normal University, Xi’an University of Posts and Telecommunications

Language: English

Topic: Neural Networks and Reservoir Computing

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Natural Science Foundation of China

Award: G5839347658