English

NECO - A scalable algorithm for NEtwork COntrol

Optimization and Control 2013-08-15 v1 Disordered Systems and Neural Networks Data Structures and Algorithms Adaptation and Self-Organizing Systems Physics and Society

Abstract

We present an algorithm for the control of complex networks and other nonlinear, high-dimensional dynamical systems. The computational approach is based on the recently-introduced concept of compensatory perturbations -- intentional alterations to the state of a complex system that can drive it to a desired target state even when there are constraints on the perturbations that forbid reaching the target state directly. Included here is ready-to-use software that can be applied to identify eligible control interventions in a general system described by coupled ordinary differential equations, whose specific form can be specified by the user. The algorithm is highly scalable, with the computational cost scaling as the number of dynamical variables to the power 2.5.

Keywords

Cite

@article{arxiv.1307.2582,
  title  = {NECO - A scalable algorithm for NEtwork COntrol},
  author = {Sean P. Cornelius and Adilson E. Motter},
  journal= {arXiv preprint arXiv:1307.2582},
  year   = {2013}
}

Comments

Source codes available at http://www.nature.com/protocolexchange/system/uploads/2647/original/neco_source.zip

R2 v1 2026-06-22T00:48:31.509Z