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Literature DB >> 26428574

Networkcontrology.

Abstract

An increasing number of complex systems are now modeled as networks of coupled dynamical entities. Nonlinearity and high-dimensionality are hallmarks of the dynamics of such networks but have generally been regarded as obstacles to control. Here, I discuss recent advances on mathematical and computational approaches to control high-dimensional nonlinear network dynamics under general constraints on the admissible interventions. I also discuss the potential of network control to address pressing scientific problems in various disciplines.

Mesh：

Year: 2015 PMID： 26428574 PMCID： PMC4592432 DOI： 10.1063/1.4931570

Source DB: PubMed Journal: Chaos ISSN： 1054-1500 Impact factor: 3.642

22 in total

Networkcontrology.

1. Emergence of scaling in random networks

2. Mechanical metamaterials with negative compressibility transitions.

3. Controlling chaos.

4. Node-to-node pinning control of complex networks.

5. Rescuing ecosystems from extinction cascades through compensatory perturbations.

6. Observability of complex systems.

7. Realistic control of network dynamics.

8. A universal scaling law between gray matter and white matter of cerebral cortex.

9. Control of Stochastic and Induced Switching in Biophysical Networks.

10. Modeling stochasticity and variability in gene regulatory networks.

1. Sex differences in network controllability as a predictor of executive function in youth.

Review 2. Brain and cognitive reserve: Translation via network control theory.

3. The Human Brain Traverses a Common Activation-Pattern State Space Across Task and Rest.

4. Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

Review 5. From Maps to Multi-dimensional Network Mechanisms of Mental Disorders.

6. A Control Theoretic Model of Adaptive Learning in Dynamic Environments.

Review 7. Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity.

8. Functional observability and target state estimation in large-scale networks.

9. Prevalence and scalable control of localized networks.

10. Control of brain network dynamics across diverse scales of space and time.