The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Synchronization of complex networks through local adaptive coupling
Abstract
Two local adaptive strategies for the synchronization of complex networks are discussed in this paper. One, termed as vertex-based, uses local adaptive coupling gains at each node in the network. The other, named edge-based, associates to each edge in the network an adaptive coupling gain, determined solely on the basis of local information. The global asymptotic stability of the synchronous evolution is proven for both strategies using appropriate Lyapunov-based techniques. The effectiveness of the adaptive methodologies presented in the paper is shown via two representative examples: adaptive consensus and the adaptive synchronization of a network on N coupled Chua’s circuits.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
Olfati-Saber, R., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834113 · Cited by 12,788
Cited by
On Pinning Synchronization of Directed and Undirected Complex Dynamical Networks
Song, Q., & Cao, J. (2010) · IEEE Transactions on Circuits and Systems I: Regular Papers · doi:10.1109/tcsi.2009.2024971 · Cited by 440
Distributed Adaptive Control of Synchronization in Complex Networks
Yu, W., DeLellis, P., Chen, G., di Bernardo, M., & Kurths, J. (2012) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2012.2183190 · Cited by 403
Self-citationSynchronization of Nonlinear Coupled Networks via Aperiodically Intermittent Pinning Control
Liu, X., & Chen, T. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2014.2311838 · Cited by 269
Metadata
- Authors
- De Lellis, P., di Bernardo, M., & Garofalo, F.
- Venue
- Chaos: An Interdisciplinary Journal of Nonlinear Science
- Publisher
- AIP Publishing
- Published
- 2008-09-01
- Volume
- 18
- Issue
- 3
- Pages
- 037110-037110
- ISSN
- 1054-1500 (ISSN-L)
- 1089-7682
- OpenAlex
- W1983692556
- Cited by
- 181
- References
- 1
- FWCI
- 24.69
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Synchronization of complex networks through local adaptive coupling. https://app.cochat.ai/papers/10.1063/1.2944236
- The paper
- De Lellis, P., di Bernardo, M., & Garofalo, F. (2008). Synchronization of complex networks through local adaptive coupling. Chaos: An Interdisciplinary Journal of Nonlinear Science. https://doi.org/10.1063/1.2944236
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
