Publications

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.

No abstract is provided for this article.

This paper initiates a systematic methodology for generating various grid multiwing hyperchaotic attractors by switching control and constructing super-heteroclinic loops from the piecewise linear hyperchaotic Lorenz system family. By linearizing the three-dimensional generalized Lorenz system family at their two symmetric equilibria and then introducing the state feedback, two fundamental four-dimensional linear systems are obtained. Moreover, a super-heteroclinic loop is constructed to connect all equilibria of the above two fundamental four-dimensional linear systems via switching control. Under some suitable conditions, various grid multiwing hyperchaotic attractors from the real world applications can be generated. Furthermore, a module-based circuit design approach is developed for realizing the designed piecewise linear grid multiwing hyperchaotic Lorenz and Chen attractors. The experimental observations validate the proposed systematic methodology for grid multiwing hyperchaotic attractors generation. Our theoretical analysis, numerical simulations and circuit implementation together show the effectiveness and universality of the proposed systematic methodology.

It is well known that in many real networks, such as brain networks and scientific collaboration networks, there exist higher order nonpairwise relations among nodes, i.e. interactions between more than two nodes at a time. This simplicial structure can be described by simplicial complexes and has an important effect on topological and dynamical properties of networks involving such group interactions. In this paper, we study analytically resistance distances in iteratively growing networks with higher order interactions characterized by the simplicial structure that is controlled by a parameter $q$. We derive exact formulas for interesting quantities about resistance distances, including Kirchhoff index, additive degree-Kirchhoff index, multiplicative degree-Kirchhoff index, as well as average resistance distance, which have found applications in various areas elsewhere. We show that the average resistance distance tends to a $q$-dependent constant, indicating the impact of simplicial organization on the structural robustness measured by average resistance distance.

No abstract is provided for this article.

This paper proposes a new model and its analysis results for time-varying structurally balanced networks. Through model transformations, the system stability problem is converted into the problem of product convergence of infinite sub-stochastic matrices (PCISM). Further, by constructing a new digraph for each interaction topology, the problem of PCISM can be handled by virtue of the properties of row-stochastic matrices. When all leaders belong to only one of the two subgroups, it is shown that the followers that are in the same subgroup as the leaders gradually enter the convex hull formed by the leaders' states, while the others gradually enter the convex hull formed by the leaders' sign-inverted states. And when both subgroups contain leaders, a sufficient algebraic graph condition is established to ensure that all followers can enter the convex hull consisting of the leaders' states and sign-inverted states together. Moreover, it is also found that the followers keep active after entering the convex hulls. Finally, the bipartite containment performance is verified by a simulation test.

No abstract is provided for this article.

A brain-controlled vehicle (BCV) is a vehicle that uses the Brain–Computer interface (BCI) to analyze the driver’s electroencephalogram (EEG) to obtain human control commands, which can help disabled people extend movement range and improve their self-independence. However, the performance of BCV is poor and the accuracy of BCI recognition varies considerably with different subjects, which severely restrict its promotion and application. To develop a better solution, with the concept of shared control, an intention preferenced fusion brain control strategy based on fuzzy logic is proposed. Firstly, based on Fuzzy Discrete Event System Supervision (FDES) theory, instructions of the driver are supervised and evaluated. At the same time, based on fuzzy logic an automatic controller which gives an automatic decision according to the cur-rent state of the vehicle is designed. Then according to the automatic decision and the correctness of the driver’s instructions, a fuzzy reasoning is made, making the final decision more in line with human intentions. In order to verify the effectiveness of the proposed method, based on our previously-designed SSMVEP platform, we conduct virtual experiments, semi-object tests and full physical tests separately for verification. Compared with others shared control schemes, it not only achieves continuous control, but the final control-making is more in line with human intentions, which can encourage users to become more involved, enhancing their self-esteem and brain functions.

Typically, a chaotic system with quadratic terms is realized based on integral summation circuits, where however operational amplifiers and multipliers are usually overused. In this brief, a new approach for simplifying such circuit implementation is proposed utilizing the inherent characteristics of a multiplier. As a result, a chaotic system with quadratic terms is realized using only a few multipliers combined with some passive linear elements. In some circumstances, an operational amplifier is employed with simple linear feedback in case the multiplier is overloaded. This simplification of chaotic circuits makes chaos generation more easily implementable, cost-effective, and hence practical for chaos-based communications.