Synchronization and an application of a novel fractional order King Cobra chaotic system

The large key space image encryption algorithm based on modulus synchronization between real and complex fractional-order dynamical systems

This paper constructs and analyzes the dynamical properties of a new fractional-order real hyper-chaotic system and its corresponding complex variable system. A thorough analysis was done by employing stability of equilibrium points, phase plots, Lyapunov spectrum, and bifurcation analysis for the consequences of varying fractional-order derivative and parameter values on the system. For the first time, a modulus synchronization scheme is proposed to synchronize real and complex fractional-order dynamical systems. Based on Lyapunov stability theory, non-linear controllers are designed to achieve the proposed modulus synchronization scheme. A new modulus synchronization encryption algorithm with a large key space size for digital images is introduced for the application. The experimental results and analysis validate the desired algorithm. Also, we compare our result of the new encryption algorithm with the previously published literature and verify the efficacy of the considered scheme. Numerical simulations are given to validate the theoretical analysis.

Emergence of bursting in a network of memory dependent excitable and spiking leech-heart neurons

Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. The diverse excitabilities of an individual neuron can be reproduced by a fractional-order biophysical model that preserves several previous memory effects. However, it is not completely clear to what extent the fractional-order dynamics changes the firing properties of excitable cells. In this article, we investigate the alternation of spiking and bursting phenomena of an uncoupled and coupled fractional leech-heart (L-H) neurons. We show that a complete graph of heterogeneous de-synchronized neurons in the backdrop of diverse memory settings (a mixture of integer and fractional exponents) can eventually lead to bursting with the formation of cluster synchronization over a certain threshold of coupling strength, however, the uncoupled L-H neurons cannot reveal bursting dynamics. Using the stability analysis in fractional domain, we demarcate the parameter space where the quiescent or steady-state emerges in uncoupled L-H neuron. Finally, a reduced-order model is introduced to capture the activities of the large network of fractional-order model neurons.

Adaptive synchronization control with optimization policy for fractional-order chaotic systems between 0 and 1 and its application in secret communication

For fractional-order chaotic systems with unequal orders between 0 and 1, a synchronization based on them and its application in secret communication are investigated in the presence of parameter uncertainty and unknown external disturbance. Firstly, through using fractional calculus theory and adaptive control method, we design a feedback controller to achieve the synchronization between the systems. Next, in order to make the controller better apply to secret communication, an optimization policy is provided for it by some performance indicator about state variables in the error system. Meanwhile, to further enhance the performance of the controller, we introduce an interval estimation (IE) strategy into quantum particle swarm optimization (QPSO) algorithm to improve it, and then this algorithm is used to optimize the controller parameters. In addition, for the security of signal transmission, a feedback mechanism with encrypted signal is offered in secret communication. Finally, by comparison, simulation experiments verify the validity and applicability of the proposed method.

Can fractional-order coexisting attractors undergo a rotational phenomenon?

This paper presents an interesting phenomenon unobserved so far in literature to the best of the authors' knowledge in fractional-order chaotic systems (FOCSs). It is the rotational phenomenon of fractional-order coexisting attractors. Another significant feature of the newly proposed FOCS is that two 2-wing chaotic attractors coexist in its fractional-order dynamics i.e. α<1. But once the system attains integer-order, the two attractors merge and evolve into a single 4-wing attractor. Furthermore, the authors have drawn its comparison with various well-known FOCSs to prove its superior features. In a novel attempt, the authors have utilised the property of simultaneous existence of coexisting attractors in the FOCS to carry out the synchronisation. A fractional-order circuit implementation with minimum components, has been performed using numerous audio signals with variable frequencies and amplitudes, as test signals. The objectives of the paper are finally achieved as the circuit implementation results are in perfect agreement with those of the theoretical analyses.

Multivariate Cryptography Based on Clipped Hopfield Neural Network

Designing secure and efficient multivariate public key cryptosystems [multivariate cryptography (MVC)] to strengthen the security of RSA and ECC in conventional and quantum computational environment continues to be a challenging research in recent years. In this paper, we will describe multivariate public key cryptosystems based on extended Clipped Hopfield Neural Network (CHNN) and implement it using the MVC (CHNN-MVC) framework operated in space. The Diffie-Hellman key exchange algorithm is extended into the matrix field, which illustrates the feasibility of its new applications in both classic and postquantum cryptography. The efficiency and security of our proposed new public key cryptosystem CHNN-MVC are simulated and found to be NP-hard. The proposed algorithm will strengthen multivariate public key cryptosystems and allows hardware realization practicality.

Synchronization of a Class of Switched Neural Networks with Time-Varying Delays via Nonlinear Feedback Control

This paper is concerned with the synchronization problem for a class of switched neural networks (SNNs) with time-varying delays. First, a new crucial lemma which includes and extends the classical exponential stability theorem is constructed. Then by using the lemma, new algebraic criteria of ψ -type synchronization (synchronization with general decay rate) for SNNs are established via the designed nonlinear feedback control. The ψ -type synchronization which is in a general framework is obtained by introducing a ψ -type function. It contains exponential synchronization, polynomial synchronization, and other synchronization as its special cases. The results of this paper are general, and they also complement and extend some previous results. Finally, numerical simulations are carried out to demonstrate the effectiveness of the obtained results.

Chaotic attractors with separated scrolls

This paper proposes a new behavior of chaotic attractors with separated scrolls while combining Julia's process with Chua's attractor and Lorenz's attractor. The main motivation of this work is the ability to generate a set of separated scrolls with different behaviors, which in turn allows us to choose one or many scrolls combined with modulation (amplitude and frequency) for secure communication or synchronization. This set seems a new class of hyperchaos because each element of this set looks like a simple chaotic attractor with one positive Lyapunov exponent, so the cardinal of this set is greater than one. This new approach could be used to generate more general higher-dimensional hyperchaotic attractor for more potential application. Numerical simulations are given to show the effectiveness of the proposed theoretical results.