1997
DOI: 10.1007/bf02405170
|View full text |Cite
|
Sign up to set email alerts
|

The attractor of the delayed functional-differential diffusion equation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3

Citation Types

0
3
0

Year Published

2001
2001
2013
2013

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(3 citation statements)
references
References 4 publications
0
3
0
Order By: Relevance
“…ential equations, partial differential equations and delay differential equations and so on [11][12][13][14][15][16][17][18]. Unfortunately, the corresponding problems for impulsive functional differential equations have not been considered prior to this work.…”
Section: Introductionmentioning
confidence: 99%
“…ential equations, partial differential equations and delay differential equations and so on [11][12][13][14][15][16][17][18]. Unfortunately, the corresponding problems for impulsive functional differential equations have not been considered prior to this work.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, a general problem of the attractivity is to discuss the attracting set and attracting basin for the impulsive systems. Some significant progress has been made in the techniques and methods of determining the attracting set and attracting basin (domain of attraction) for the continuous systems described by ordinary differential equations [7,17] and functional differential 2 Attractivity of impulsive differential equations equations [5,9,13,15,18]. However, so far the corresponding problems for impulsive delay differential equations have not been considered.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, the invariant and attracting sets of dynamical systems have attracted considerable attention, and various interesting results on this problem have been reported (Sawano 1980, Marion 1987, GyoÈ ri 1990, Xiang 1991, Xu 1996, Hale 1997, Razgulin 1997). However, not much has been developed in the direction of the Hop® eld neural networks system.…”
Section: Introductionmentioning
confidence: 99%