Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Shunting inhibitory cellular neural networks with strongly unpredictable oscillations
Date
2020-10-01
Author
Akhmet, Marat
Tleubergenova, Madina
Zhamanshin, Akylbek
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
324
views
0
downloads
Cite This
The paper considers a new type of solutions for shunting inhibitory cellular neural networks (SICNNs), strongly unpredictable oscillations. The conditions for the existence, uniqueness and stability of the solutions are determined. Numerical examples are given to show the feasibility of the obtained results.
Subject Keywords
Modelling and Simulation
,
Applied Mathematics
,
Numerical Analysis
URI
https://hdl.handle.net/11511/48918
Journal
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
DOI
https://doi.org/10.1016/j.cnsns.2020.105287
Collections
Department of Mathematics, Article
Suggestions
OpenMETU
Core
Domain-Structured Chaos in a Hopfield Neural Network
Akhmet, Marat (World Scientific Pub Co Pte Lt, 2019-12-30)
In this paper, we provide a new method for constructing chaotic Hopfield neural networks. Our approach is based on structuring the domain to form a special set through the discrete evolution of the network state variables. In the chaotic regime, the formed set is invariant under the system governing the dynamics of the neural network. The approach can be viewed as an extension of the unimodality technique for one-dimensional map, thereby generating chaos from higher-dimensional systems. We show that the dis...
Non-autonomous equations with unpredictable solutions
Akhmet, Marat (Elsevier BV, 2018-06-01)
To make research of chaos more amenable to investigating differential and discrete equations, we introduce the concepts of an unpredictable function and sequence. The topology of uniform convergence on compact sets is applied to define unpredictable functions [1,2]. The unpredictable sequence is defined as a specific unpredictable function on the set of integers. The definitions are convenient to be verified as solutions of differential and discrete equations. The topology is metrizable and easy for applica...
Unstructured grid generation and a simple triangulation algorithm for arbitrary 2-D geometries using object oriented programming
Karamete, BK; Tokdemir, Turgut; Ger, M (Wiley, 1997-01-30)
This paper describes the logic of a dynamic algorithm for a general 2D Delaunay triangulation of arbitrarily prescribed interior and boundary nodes. The complexity of the geometry is completely arbitrary. The scheme is free of specific restrictions on the input of the geometrical data. The scheme generates triangles whose associated circumcircles contain 'no nodal points except their vertices. There is no predefined limit for the number of points and the boundaries. The direction of generation of the triang...
Computational modeling of electrocardiograms: A finite element approach toward cardiac excitation
Kotikanyadanam, Mohan; Göktepe, Serdar; Kuhl, Ellen (Wiley, 2010-05-01)
The objective of this work is the computational simulation of a patient-specific electrocardiogram (EKG) using a novel, robust, efficient, and modular finite element-based simulation tool for cardiac electrophysiology. We apply a two-variable approach in terms of a fast action potential and a slow recovery variable, whereby the latter phenomenologically summarizes the concentration of ionic currents. The underlying algorithm is based on a staggered solution scheme in which the action potential is introduced...
Modern tools for the time-discrete dynamics and optimization of gene-environment networks
DEFTERLİ, ÖZLEM; Fuegenschuh, Armin; Weber, Gerhard Wilhelm (Elsevier BV, 2011-12-01)
In this study, we discuss the models of genetic regulatory systems, so-called gene-environment networks. The dynamics of such kind of systems are described by a class of time-continuous ordinary differential equations having a general form (E) over dot = M(E)E, where E is a vector of gene-expression levels and environmental factors and M(E) is the matrix having functional entries containing unknown parameters to be optimized. Accordingly, time-discrete versions of that model class are studied and improved b...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Akhmet, M. Tleubergenova, and A. Zhamanshin, “Shunting inhibitory cellular neural networks with strongly unpredictable oscillations,”
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48918.