Linear active control algorithm to synchronize a nonlinear HIV/AIDS dynamical system

Chaos synchronization between two chaotic systems happens when the trajectory of one of the system asymptotically follows the trajectory of another system due to forcing or due to coupling.This research paper addresses the synchronization problem of an In-host Model for HIV/AIDS dynamics using the Linear Active Control Technique.In this study, using the Linear Active Control Algorithm based on the Lyapunov stability theory, the synchronization between two identical HIV/AIDS chaotic systems and the switching synchronization between two different HIV/AIDS and Qi 4-D chaotic systems has been observed. Further, it has been shown that the proposed schemes have excellent transient performance and analytically as well as graphically found that the synchronization is globally exponential stable.Numerical simulations are carried out to demonstrate the efficiency of the proposed approach that support the analytical results and illustrated the possible scenarios for synchronization. All simulations have been done using Mathematica 9

A New Chaotic Map for Secure Transmission

The secure communication through synchronization between two identic chaotic systems have recently gained a lot of interest. To implement a robust secure system based on synchronization, there is always a need to generate new discrete dynamical systems and investigate their performances in terms of amount of randomness they have and the ability to achieve synchronization smoothly. In this work, a new chaotic system, named Nahrain, is proposed and tested for the possible use in secure transmission via chaos synchronization as well as in cryptography applications. The performance of the proposed chaotic system is tested using 0-1 test, while NIST suite tests are used to check the randomness statistical properties. The nonlinear control laws are used to verify the synchronization of master-slave parts of the proposed system. The simulation results show that Nahrain system has chaotic behavior and synchronizable, while the equivalent binary sequence of the system has excellent randomness statistical properties. The numerical results obtained using MATLAB for 0-1 test was 0.9864, and for frequency test was 0.4202, while for frequency test within a block was 0.4311. As a result, the new proposed system can be used to develop efficient encryption and synchronization algorithms for multimedia secure transmission applications

Effect of Random Parameter Switching on Commensurate Fractional Order Chaotic Systems

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.The paper explores the effect of random parameter switching in a fractional order (FO) unified chaotic system which captures the dynamics of three popular sub-classes of chaotic systems i.e. Lorenz, Lu and Chen's family of attractors. The disappearance of chaos in such systems which rapidly switch from one family to the other has been investigated here for the commensurate FO scenario. Our simulation study show that a noise-like random variation in the key parameter of the unified chaotic system along with a gradual decrease in the commensurate FO is capable of suppressing the chaotic fluctuations much earlier than that with the fixed parameter one. The chaotic time series produced by such random parameter switching in nonlinear dynamical systems have been characterized using the largest Lyapunov exponent (LLE) and Shannon entropy. The effect of choosing different simulation techniques for random parameter FO switched chaotic systems have also been explored through two frequency domain and three time domain methods. Such a noise-like random switching mechanism could be useful for stabilization and control of chaotic oscillation in many real-world applications

Nonlinear dynamics: challenges and perspectives

The study of nonlinear dynamics has been an active area of research since 1960s, after certain path-breaking discoveries, leading to the concepts of solitons, integrability, bifurcations, chaos and spatio-temporal patterns, to name a few. Several new techniques and methods have been developed to understand nonlinear systems at different levels. Along with these, a multitude of potential applications of nonlinear dynamics have also been enunciated. In spite of these developments, several challenges, some of them fundamental and others on the efficacy of these methods in developing cutting edge technologies, remain to be tackled. In this article, a brief personal perspective of these issues is presented

Dynamical systems applied to consciousness and brain rhythms in a neural network

This thesis applies the great advances of modern dynamical systems theory (DST) to consciousness. Consciousness, or subjective experience, is faced here in two different ways: from the global dynamics of the human brain and from the integrated information theory (IIT), one of the currently most prestigious theories on consciousness. Before that, a study of a numerical simulation of a network of individual neurons justifies the use of the Lotka-Volterra model for neurons assemblies in both applications. All these proposals are developed following this scheme: • First, summarizing the structure, methods and goal of the thesis. • Second, introducing a general background in neuroscience and the global dynamics of the human brain to better understand those applications. • Third, conducting a study of a numerically simulated network of neurons. This network, which displays brain rhythms, can be employed, among other objectives, to justify the use of the Lotka-Volterra model for applications. • Fourth, summarizing concepts from the mathematical DST such as the global attractor and its informational structure, in addition to its particularization to a Lotka-Volterra system. • Fifth, introducing the new mathematical concepts of model transform and instantaneous parameters that allow the application of simple mathematical models such as Lotka-Volterra to complex empirical systems as the human brain. • Sixth, using the model transform, and specifically the Lotka-Volterra transform, to calculate global attractors and informational structures in global dynamics of the human brain. • Seventh, knowing the probably most prestigious theory on consciousness, the IIT developed by G. Tononi. • Eighth, using informational structures to develop a continuous version of IIT. And ninth, establishing some final conclusions and commenting on new open questions from this work. These nine points of this scheme correspond to the nine chapters of this thesis

A guided tour of asynchronous cellular automata

Research on asynchronous cellular automata has received a great amount of attention these last years and has turned to a thriving field. We survey the recent research that has been carried out on this topic and present a wide state of the art where computing and modelling issues are both represented.Comment: To appear in the Journal of Cellular Automat

Synchronization of Coupled Different Chaotic FitzHugh-Nagumo Neurons with Unknown Parameters under Communication-Direction-Dependent Coupling

This paper investigates the chaotic behavior and synchronization of two different coupled chaotic FitzHugh-Nagumo (FHN) neurons with unknown parameters under external electrical stimulation (EES). The coupled FHN neurons of different parameters admit unidirectional and bidirectional gap junctions in the medium between them. Dynamical properties, such as the increase in synchronization error as a consequence of the deviation of neuronal parameters for unlike neurons, the effect of difference in coupling strengths caused by the unidirectional gap junctions, and the impact of large time-delay due to separation of neurons, are studied in exploring the behavior of the coupled system. A novel integral-based nonlinear adaptive control scheme, to cope with the infeasibility of the recovery variable, for synchronization of two coupled delayed chaotic FHN neurons of different and unknown parameters under uncertain EES is derived. Further, to guarantee robust synchronization of different neurons against disturbances, the proposed control methodology is modified to achieve the uniformly ultimately bounded synchronization. The parametric estimation errors can be reduced by selecting suitable control parameters. The effectiveness of the proposed control scheme is illustrated via numerical simulations