Bifurcation Investigating of a Fractional Neural Networks Involving Incommensurate Delays

In this current article, an issue of Hopf bifurcation control about a novel fractional-order network owing multiple delays and feedback gain is formulated. The bifurcation parameter time delay is selected as the bifurcation parameter. The stability conditions and the bifurcation point are established. Ultimately, a simulation example is provided to verify the validity of the obtained newly results. The important results obtained in this paper have important theoretical significance and application value for the regulation and control of fractional-order neural networks with time-delay.

Authors

Institutions

Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/icarce63054.2024.00040
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bifurcation Investigating of a Fractional Neural Networks Involving Incommensurate Delays

Xin Hu Wang, Yongfeng Zhang, Hui Zhang, Tongxing Li et al.
Neural Networks and Applications
article

Bifurcation Investigating of a Fractional Neural Networks Involving Incommensurate Delays

Xin Hu Wang, Yongfeng Zhang, Hui Zhang, Tongxing Li, Yan Wang
article en

Abstract

In this current article, an issue of Hopf bifurcation control about a novel fractional-order network owing multiple delays and feedback gain is formulated. The bifurcation parameter time delay is selected as the bifurcation parameter. The stability conditions and the bifurcation point are established. Ultimately, a simulation example is provided to verify the validity of the obtained newly results. The important results obtained in this paper have important theoretical significance and application value for the regulation and control of fractional-order neural networks with time-delay.

Taishan University (CN), Shandong Jianzhu University (CN), Shandong Agricultural University (CN)
Youth Innovation Technology Project of Higher School in Shandong Province
Openalex Percentile: Top 73%
Neural Networks and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Bifurcation Investigating of a Fractional Neural Networks Involving Incommensurate Delays — Xin Hu Wang, Yongfeng Zhang, et al. · (2024) | TGRS Research Map | TGRS