Iterative Sequences of the Localization Method

The conditions of positive invariance and compactness of localizing sets and extended localizing sets are proved. The necessary condition for the existence of an attractor in the system is obtained. The concept of an iterative sequence of extended localizing sets is introduced and a condition is obtained under which its elements are positively invariant compact sets and give an estimate of the attraction set. Using the obtained results, the behavior of the trajectories of a three-dimensional system is investigated for acceptable values of its parameters. The conditions of global stability of one of its equilibrium points are found and the set of attraction of another equilibrium point is indicated.

Authors

Institutions

Publication Details

Journal
Differential Equations
Published
2024-11-01
DOI
https://doi.org/10.1134/s001226612411003x
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Iterative Sequences of the Localization Method

А. П. Крищенко
Differential Equations
Neural Networks and Applications
article

Iterative Sequences of the Localization Method

А. П. Крищенко
article en

Abstract

The conditions of positive invariance and compactness of localizing sets and extended localizing sets are proved. The necessary condition for the existence of an attractor in the system is obtained. The concept of an iterative sequence of extended localizing sets is introduced and a condition is obtained under which its elements are positively invariant compact sets and give an estimate of the attraction set. Using the obtained results, the behavior of the trajectories of a three-dimensional system is investigated for acceptable values of its parameters. The conditions of global stability of one of its equilibrium points are found and the set of attraction of another equilibrium point is indicated.

Differential EquationsVol. 60(11)
Bauman Moscow State Technical University (RU)
Openalex Percentile: Top 75%
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.