Exponential stability of gene regulatory networks with distributed delays

This paper explores the global exponential stability (GES) for a class of genetic regulatory networks (GRNs) with distributed time-varying delays. Firstly, we establish a new class of GRNs with recent-history distributed time-varying delays, which can be useful for better understanding of GRNs dynamics more precisely. Then, to simplify the complexity of the main results, a suitable Lyapunov functional is constructed with the help of Lyapunov stability theory, and some new delay-dependent exponential stability conditions for the considered GRNs are derived. Different from other papers, this paper presents novel results that are easy to solve and new insights into GES of GRNs. Finally, two standard numerical examples along with their simulation analysis are presented to illustrate the effectiveness of theoretical results.

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Publication Details

Journal
Journal of Mathematics and Computer Science
Published
2024-12-13
DOI
https://doi.org/10.22436/jmcs.038.02.07
Citations
1
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.23

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article

Exponential stability of gene regulatory networks with distributed delays

S. Logeswari, R. Sriraman
1 citations
Journal of Mathematics and Computer Science
Gene Regulatory Network Analysis
0.23
article

Exponential stability of gene regulatory networks with distributed delays

S. Logeswari, R. Sriraman
article en
1 citations

Abstract

This paper explores the global exponential stability (GES) for a class of genetic regulatory networks (GRNs) with distributed time-varying delays. Firstly, we establish a new class of GRNs with recent-history distributed time-varying delays, which can be useful for better understanding of GRNs dynamics more precisely. Then, to simplify the complexity of the main results, a suitable Lyapunov functional is constructed with the help of Lyapunov stability theory, and some new delay-dependent exponential stability conditions for the considered GRNs are derived. Different from other papers, this paper presents novel results that are easy to solve and new insights into GES of GRNs. Finally, two standard numerical examples along with their simulation analysis are presented to illustrate the effectiveness of theoretical results.

Journal of Mathematics and Computer Science
SRM Institute of Science and Technology (IN)
Science and Engineering Research Board
Openalex Percentile: Top 40%
Gene Regulatory Network Analysis
0.23
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Exponential stability of gene regulatory networks with distributed delays — S. Logeswari, R. Sriraman · Journal of Mathematics and Computer Science (2024) | TGRS Research Map | TGRS