Abstract
A unified approach to the analysis of synchronization for complex dynamical networks, i.e., networks of partial-state coupled linear systems and networks of full-state coupled nonlinear oscillators, is introduced. It is shown that the developed analysis can be used to describe the difference between the state of each node and the weighted sum of the states of those nodes playing the role of leaders in the networks, thus making it feasible to consider the error dynamics for the whole network system. Different from the other various methods given in the existing literature, the analysis employed in this paper is demonstrated successfully in not only providing the consistent convergence analysis with much simpler form, but also explicitly specifying the convergence rate.
| Original language | English |
|---|---|
| Pages (from-to) | 510-521 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Neural Networks and Learning Systems |
| Volume | 26 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2015 |
Keywords
- linear systems
- neural networks (computer science)
- nonlinear oscillators
- synchronization
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