scholarly journals Theorems and Application of Local Activity of CNN with Five State Variables and One Port

2012 ◽  
Vol 2012 ◽  
pp. 1-13
Author(s):  
Gang Xiong ◽  
Xisong Dong ◽  
Li Xie ◽  
Thomas Yang
Keyword(s):  
Bifurcation Diagram ◽  
Complex Dynamics ◽  
Nonlinear Dynamical Systems ◽  
Reaction Diffusion ◽  
Cellular Neural Network ◽  
State Variables ◽  
Nonlinear Dynamical ◽  
Local Activity ◽  
Homogeneous Lattice ◽  
Coupled Cells

Coupled nonlinear dynamical systems have been widely studied recently. However, the dynamical properties of these systems are difficult to deal with. The local activity of cellular neural network (CNN) has provided a powerful tool for studying the emergence of complex patterns in a homogeneous lattice, which is composed of coupled cells. In this paper, the analytical criteria for the local activity in reaction-diffusion CNN with five state variables and one port are presented, which consists of four theorems, including a serial of inequalities involving CNN parameters. These theorems can be used for calculating the bifurcation diagram to determine or analyze the emergence of complex dynamic patterns, such as chaos. As a case study, a reaction-diffusion CNN of hepatitis B Virus (HBV) mutation-selection model is analyzed and simulated, the bifurcation diagram is calculated. Using the diagram, numerical simulations of this CNN model provide reasonable explanations of complex mutant phenomena during therapy. Therefore, it is demonstrated that the local activity of CNN provides a practical tool for the complex dynamics study of some coupled nonlinear systems.

scholarly journals SOME ANALYTICAL CRITERIA FOR LOCAL ACTIVITY OF TWO-PORT CNN WITH THREE OR FOUR STATE VARIABLES: ANALYSIS AND APPLICATIONS

2002 ◽  
Vol 12 (05) ◽  
pp. 931-963 ◽  
Author(s):  
LEQUAN MIN ◽  
NA YU
Keyword(s):  
Cell Model ◽  
Reaction Diffusion ◽  
State Variables ◽  
Periodic Patterns ◽  
Local Activity ◽  
Nonlinear Network ◽  
Edge Of Chaos ◽  
Excitable Membranes ◽  
Coupled Cells ◽  
Complex Patterns

The local activity principle of the Cellular Nonlinear Network (CNN) introduced by Chua [1997] has provided a powerful tool for studying the emergence of complex patterns in a homogeneous lattice formed by coupled cells. This paper presents some analytical criteria for the local activity of two-port CNN cells with three or four state variables. As a first application, a coupled excitable cell model (ECM) CNN is introduced, which has cells defined by the Chay equations representing ionic events in excitable membranes in terms of a Hodgkin–Huxley type formalism. The bifurcation diagram of the ECM CNN supplies a possible explanation for the mechanism of arrhythmia (from normal to abnormal until stopping) of excitable cells: the cell parameter is changed from an active unstable domain to an edge of chaos. The member potentials along fibers are simulated numerically, where oscillatory patterns, chaotic patterns as well as convergent patterns are observed. As a second application, a smoothed Chua's circuit (SCC) CNN with two ports is presented, whose prototype has been introduced by Chua as a dual-layer two-dimensional reaction–diffusion CNN in order to obtain Turing patterns. The bifurcation diagrams of the SCC CNN are the same as those with one port, which have only active unstable domains and edges of chaos. Numerical simulations show that in the active unstable parameter domains, the evolutions of the patterns of the state variables of the SCC CNNs can exhibit divergence, periodicity and chaos, where, in the parameter domains located in the edge of chaos, periodic patterns and divergent patterns are observed. These results demonstrate once again the effectiveness of the local activity theory in choosing the parameters for the emergence of complex patterns of CNNs.

scholarly journals Chaotic Dynamics and Complexity in Real and Physical Systems

2021 ◽  
Author(s):  
Mrinal Kanti Das ◽  
Lal Mohan Saha
Keyword(s):  
Complex Dynamics ◽  
Nonlinear Dynamical Systems ◽  
Neuronal Dynamics ◽  
Financial Model ◽  
Nonlinear Dynamical ◽  
Physical Systems ◽  
Investment Demand ◽  
Model Complex ◽  
Artificial Neural Network Ann ◽  
Emergence Of Chaos

Emergence of chaos and complex behavior in real and physical systems has been discussed within the framework of nonlinear dynamical systems. The problems investigated include complexity of Child’s swing dynamics , chaotic neuronal dynamics (FHN model), complex Food-web dynamics, Financial model (involving interest rate, investment demand and price index) etc. Proper numerical simulations have been carried out to unravel the complex dynamics of these systems and significant results obtained are displayed through tables and various plots like bifurcations, attractors, Lyapunov exponents, topological entropies, correlation dimensions, recurrence plots etc. The significance of artificial neural network (ANN) framework for time series generation of some dynamical system is suggested.

Edge of Chaos and Local Activity Domain of the Gierer–Meinhardt CNN

1998 ◽  
Vol 08 (12) ◽  
pp. 2321-2340 ◽  
Author(s):  
Radu Dogaru ◽  
Leon O. Chua
Keyword(s):  
Activity Theory ◽  
Parameter Space ◽  
Cell Parameter ◽  
Reaction Diffusion ◽  
Specific Reaction ◽  
Local Activity ◽  
Nonlinear Network ◽  
Edge Of Chaos ◽  
Homogeneous Lattice ◽  
Activity Domain

This paper present an application of the local activity theory [Chua, 1998] to a specific reaction–diffusion cellular nonlinear network (CNN) with cells defined by the model of morphogenesis first proposed in [Gierer & Meinhardt, 1972]. Both the local activity domain and a subset called the "edge of chaos" are identified in the cell parameter space. Within these domains, various cell parameter points were selected to illustrate the effectiveness of the local activity theory in choosing the parameters for the emergence of complex (static and dynamic) patterns in a homogeneous lattice formed by coupled locally active cells.

OSCILLATIONS ON THE EDGE OF CHAOS VIA DISSIPATION AND DIFFUSION

2007 ◽  
Vol 17 (05) ◽  
pp. 1531-1573 ◽  
Author(s):  
MAKOTO ITOH ◽  
LEON O. CHUA
Keyword(s):  
Dynamical Systems ◽  
Nonlinear Dynamical Systems ◽  
Reaction Diffusion ◽  
Coupled System ◽  
Reaction Diffusion Equations ◽  
Nonlinear Dynamical ◽  
Edge Of Chaos ◽  
Secondary Purpose ◽  
Spatio Temporal ◽  
And Diffusion

The primary purpose of this paper is to show that simple dissipation can bring about oscillations in certain kinds of asymptotically stable nonlinear dynamical systems; namely when the system is locally active where the dissipation is introduced. Furthermore, if these nonlinear dynamical systems are coupled with appropriate choice of diffusion coefficients, then the coupled system can exhibit spatio-temporal oscillations. The secondary purpose of this paper is to show that spatio-temporal oscillations can occur in spatially discrete reaction diffusion equations operating on the edge of chaos, provided the array size is sufficiently large.

ANALYTICAL CRITERIA FOR LOCAL ACTIVITY AND APPLICATIONS TO THE OREGONATOR CNN

2000 ◽  
Vol 10 (01) ◽  
pp. 25-71 ◽  
Author(s):  
LEQUAN MIN ◽  
KENNETH R. CROUNSE ◽  
LEON O. CHUA
Keyword(s):  
Cell Parameter ◽  
High Energy ◽  
Reaction Model ◽  
Cell Parameters ◽  
Local Activity ◽  
Nonlinear Network ◽  
Edge Of Chaos ◽  
Homogeneous Lattice ◽  
Coupled Cells ◽  
Emergence Of Complexity

This paper presents analytic criteria for local activity in one-port Cellular Nonlinear Network (CNN) cells [Chua, 1997, 1999], and gives the applications to the Oregonator CNN defined by the kinetic chemical reaction model of morphogenesis first introduced in [Field & Noyes, 1974]. Locally active domains, locally passive domains, and the edge of chaos are identified in the cell parameter space. Computer simulations of the dynamics of several Oregonator CNN's with specific selected cell parameters in the above-mentioned domains show genesis and the emergence of complexity. Furthermore, a novel phenomena is observed that "extremely high energy" is concentrated only on a few cells in the dynamic patterns of some Oregonator CNN's whose cell parameters are located in active domains; furthermore, relaxation oscillations and "transient oscillations" can exist if the cell parameters of the Oregonator CNN are located nearby or on the edge of chaos. This research illustrates once again the effectiveness of the local activity theory in choosing the system parameters for the emergence of complex patterns (static and dynamic) in a homogeneous lattice formed by coupled cells.

A sequential importance sampling filter with a new proposal distribution for state and parameter estimation of nonlinear dynamical systems

2007 ◽  
Vol 464 (2089) ◽  
pp. 25-47 ◽  
Author(s):  
Shuva J Ghosh ◽  
C.S Manohar ◽  
D Roy
Keyword(s):  
Dynamical Systems ◽  
Parameter Identification ◽  
Importance Sampling ◽  
Nonlinear Dynamical Systems ◽  
Gaussian White Noise ◽  
Sequential Importance Sampling ◽  
State Variables ◽  
Nonlinear Dynamical ◽  
Taylor Expansions ◽  
Non Gaussian

The problem of estimating parameters of nonlinear dynamical systems based on incomplete noisy measurements is considered within the framework of Bayesian filtering using Monte Carlo simulations. The measurement noise and unmodelled dynamics are represented through additive and/or multiplicative Gaussian white noise processes. Truncated Ito–Taylor expansions are used to discretize these equations leading to discrete maps containing a set of multiple stochastic integrals. These integrals, in general, constitute a set of non-Gaussian random variables. The system parameters to be determined are declared as additional state variables. The parameter identification problem is solved through a new sequential importance sampling filter. This involves Ito–Taylor expansions of nonlinear terms in the measurement equation and the development of an ideal proposal density function while accounting for the non-Gaussian terms appearing in the governing equations. Numerical illustrations on parameter identification of a few nonlinear oscillators and a geometrically nonlinear Euler–Bernoulli beam reveal a remarkably improved performance of the proposed methods over one of the best known algorithms, i.e. the unscented particle filter.

Edge of Chaos and Local Activity Domain of the Brusselator CNN

1998 ◽  
Vol 08 (06) ◽  
pp. 1107-1130 ◽  
Author(s):  
Radu Dogaru ◽  
Leon O. Chua
Keyword(s):  
Activity Theory ◽  
Parameter Space ◽  
Cell Parameter ◽  
Reaction Diffusion ◽  
Specific Reaction ◽  
Local Activity ◽  
Nonlinear Network ◽  
Edge Of Chaos ◽  
Homogeneous Lattice ◽  
Activity Domain

This paper presents an application of the local activity theory [Chua, 1998] to a specific reaction–diffusion cellular nonlinear network (CNN) with cells defined by a trimolecular model, called the Brusselator. Both the local activity domain and a subset called the "edge of chaos" are identified in the cell parameter space. Within these domains, various cell parameter points were selected to illustrate the effectiveness of the local activity theory in choosing the parameters for the emergence of complex (static and dynamic) patterns in a homogeneous lattice formed by coupled locally active cells.

Some Analytical Criteria for Local Activity of Three-Port CNN with Four State Variables: Analysis and Applications

2003 ◽  
Vol 13 (08) ◽  
pp. 2189-2239 ◽  
Author(s):  
Lequan Min ◽  
Jingtao Wang ◽  
Xisong Dong ◽  
Guanrong Chen
Keyword(s):  
Numerical Simulations ◽  
Wide Spectrum ◽  
Immune Surveillance ◽  
Reaction Diffusion ◽  
Diffusion Control ◽  
State Variables ◽  
Bifurcation Diagrams ◽  
Cell Parameters ◽  
Local Activity ◽  
Nonlinear Network

This paper presents some analytical criteria for local activity principle in reaction–diffusion Cellular Nonlinear Network (CNN) cells [Chua, 1997, 1999] that have four local state variables with three ports. As a first application, a cellular nonlinear network model of tumor growth and immune surveillance against cancer (GISAC) is discussed, which has cells defined by the Lefever–Erneaux equations, representing the densities of alive and dead cancer cells, as well as the number of free and bound cytotoxic cells, per unit volume. Bifurcation diagrams of the GISAC CNN provide possible explanations for the mechanism of cancer diffusion, control, and elimination. Numerical simulations show that oscillatory patterns and convergent patterns (representing cancer diffusion and elimination, respectively) may emerge if selected cell parameters are located nearby or on the edge of the chaos domain. As a second application, a smoothed Chua's oscillator circuit (SCC) CNN with three ports is studied, for which the original prototype was introduced by Chua as a dual-layer two-dimensional reaction–diffusion CNN with three state variables and two ports. Bifurcation diagrams of the SCC CNN are computed, which only demonstrate active unstable domains and edges of chaos. Numerical simulations show that evolution of patterns of the state variables of the SCC CNN can exhibit divergence, periodicity, and chaos; and the second and the fourth state variables of the SCC CNNs may exhibit generalized synchronization. These results demonstrate once again Chua's assertion that a wide spectrum of complex behaviors may exist if the corresponding CNN cell parameters are chosen in or nearby the edge of chaos.

TAILORING THE BIFURCATION DIAGRAM OF NONLINEAR DYNAMICAL SYSTEMS: AN OPTIMIZATION BASED APPROACH

2010 ◽  
Vol 20 (04) ◽  
pp. 1027-1040 ◽  
Author(s):  
PIETRO ALTIMARI ◽  
ERASMO MANCUSI ◽  
MARIO DI BERNARDO ◽  
LUCIA RUSSO ◽  
SILVESTRO CRESCITELLI
Keyword(s):  
Bifurcation Diagram ◽  
Nonlinear Dynamical Systems ◽  
Feedforward Control ◽  
Nonlinear Dynamical System ◽  
Chemical Reactor ◽  
Control Law ◽  
Control Laws ◽  
Nonlinear Dynamical ◽  
Output Behavior ◽  
Objective Functional

Bifurcation tailoring is a method developed to design control laws modifying the bifurcation diagram of a nonlinear dynamical system to a desired one. In its original formulation, this method does not account for the possible presence of constraints on state and/or manipulated inputs. In this paper, a novel formulation of the bifurcation tailoring method overcoming this limitation is presented. In accordance with the proposed approach, a feedforward control law generating an optimal bifurcation diagram is computed by constrained minimization of an objective functional. Then, a feedback control system enforcing stability of the computed equilibrium branch is designed. In this context, bifurcation analysis is exploited to select feedback controller parameters ensuring desired output behavior and, at the same time, preventing the occurrence of multistability. The method is numerically validated on the problem of tailoring the bifurcation diagram of an exothermic chemical reactor.

scholarly journals Finite Time Synchronization of Extended Nonlinear Dynamical Systems Using Local Coupling

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
A. Acosta ◽  
P. García ◽  
H. Leiva ◽  
A. Merlitti
Keyword(s):  
Finite Time ◽  
Time Synchronization ◽  
Nonlinear Dynamical Systems ◽  
Reaction Diffusion ◽  
Coupling Function ◽  
Reaction Diffusion Equations ◽  
Nonlinear Dynamical ◽  
Synchronization Problem ◽  
Driven System ◽  
Directional Coupling

We consider two reaction-diffusion equations connected by one-directional coupling function and study the synchronization problem in the case where the coupling function affects the driven system in some specific regions. We derive conditions that ensure that the evolution of the driven system closely tracks the evolution of the driver system at least for a finite time. The framework built to achieve our results is based on the study of an abstract ordinary differential equation in a suitable Hilbert space. As a specific application we consider the Gray-Scott equations and perform numerical simulations that are consistent with our main theoretical results.

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