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In this paper, we consider an insurance company which has the option of investing in a risky asset and a risk-free asset, whose price parameters are driven by a finite state Markov chain. The risk process of the insurance company is modeled as a diffusion process whose diffusion and drift parameters switch over time according to the same Markov chain. We study the Markov-modulated mean-variance problem for the insurer and derive explicitly the closed form of the efficient strategy and efficient frontier. In the case of no regime switching, we can see that the efficient frontier in our paper coincides with that of [10] when there is no pure jump.

In this paper, synchronization of delayed fuzzy cellular neural networks has been considered. By construction a suitable Lyapunov functional and utilizing some inequality techniques, some sufficient conditions for synchronization of such a system are obtained. Simulation results are given to justify the theoretical analysis in this paper.

In this paper, we prove the controllability of a quasi-linear heat equation involving gradient terms with Fourier boundary conditions in a bounded domain of ℝN. The proofs of the main results in this paper involve such inequalities and rely on the study of these linear problems and appropriate fixed point arguments.

In the control signal process theory, the state equation is an important approach for modelling, analyzing and designing a wide range of systems. Furthermore, the state equation is often the most efficient form from the standpoint of computer simulation for highly complex systems. The existing researches exploit the fact that for networks containing dependent sources, bridging elements and coupling elements, the derivation of the closed-form state equation becomes rather complicated. On the other hand, a simple and valuable unifying approach of finding the state equations for complicated physical systems is successfully presented in the paper. The new unifying approach needs only the substitution theorem and the author’s invented simple matrix operations. The main fascinating peculiarity of this approach is exposed in its systematic, graphic and human structure that improves the shortcomings of those traditional approaches. One comparative example is proposed to show the distinguished advantages our method offers over existing methods. In order to demonstrate the practical applicability, the paper has investigated an electronic operational-amplifier circuit that can be easily stabilized by our approach.

This paper introduces a modified Lu chaotic system, and some basic dynamical properties are studied. Based on these properties, we present hybrid dislocated control method for stabilizing chaos to unstable equilibrium and limit cycle. In addition, based on the Lyapunov stability theorem, general hybrid projective dislocated synchronization (GHPDS) is proposed, which includes complete dislocated synchronization, dislocated anti-synchronization and projective dislocated synchronization as its special item. The drive and response systems discussed in this paper can be strictly different dynamical systems (including different dimensional systems). As examples, the modified Lu chaotic system, Chen chaotic system and hyperchaotic Chen system are discussed. Numerical simulations are given to show the effectiveness of these methods.

This paper studies the problem of delay-dependent robust stability for uncertain neutral system with mixed delays. Based on a novel augmented Lyapunov functional approach and linear matrix inequality technology, a new delay-dependent stability condition is derived. Since no restriction on the derivative of the time-varying discrete delay is needed, the criteria proposed in this paper are less conservative than some previous approaches. Numerical examples are given to show the effectiveness of the proposed methods and the influence of uncertainties to the stability of the neutral system.

At first, the paper described a brief history of communication in China. In 2008, the third generation (3G) telecommunication technologies began to develop. In Chinese 3G telecommunication market, there are three oligopolistic competitors. In order to study competing process of the triopoly, the paper considered a Bertrand model with bounded rational. A triopoly game is modeled by three nonlinear difference equations. By using the theory of bifurcations of dynamical systems, the existence and stability for the equilibria of this system were obtained. Numerical simulations were used to show bifurcations diagrams, the maximum Lyapunov exponent and sensitive dependence on initial conditions. We observed that increasing the speed of adjustment of bounded rational player might change the stability of Nash equilibrium point and cause bifurcation and chaos to occur. Thus, it will be difficult to make strategy and to forecast for each enterprise. It might cause the telecom markets to be irregular. The analysis and results in this paper are important for Chinese telecommunication markets, the same to mathematics.

In this paper, reaction–diffusion Cohen–Grossberg neural networks (RDCGNN) with varying delay and Robin boundary conditions is studied by Halanay inequality and Young inequality, and sufficient conditions are given to guarantee global exponential stability of the equilibrium point. The proof of main result improves the earlier finding. Moreover, RDCGNN with large impulse also is investigated. Finally, a numerical example is given to show the effectiveness of the results in this paper.

In this paper, we have tried to apply the concepts of fuzzy set to Lie groups and fuzzy differential invariant (FDI) in order to provide suitable conditions for applying Lie symmetry method in solving fuzzy differential equations (FDEs). For this, we define a C 1 -fuzzy submanifold and fuzzy immersion with some examples. In main section, we defined the fuzzy Lie group and some its relative concepts such as fuzzy transformation group and fuzzy G-invariant. The goal of this paper is to introduce and study new defining for fuzzy Lie group and fuzzy differential invariant (FDI). Also, some illustrative examples are given.

The construction of cryptographically strong substitution boxes (S-boxes) is an important concern in designing secure cryptosystems. The key-dependent S-boxes designed using chaotic maps have received increasing attention in recent years. However, the key space of such S-boxes does not seem to be sufficiently large due to the limited parameter range of discretized chaotic maps. In this paper, we propose a new key-dependent S-box based on the iteration of continuous chaotic maps. We explore the continuous-valued state space of chaotic systems, and devise the discrete mapping between the input and the output of the S-box. A key-dependent S-box is constructed with the logistic map in this paper. We show that its key space could be much larger than the current key-dependent chaotic S-boxes.

Image encryption is somehow different from text encryption due to some inherent features of image such as bulk data capacity and high correlation among pixels, which are generally difficult to handle by conventional methods. The desirable cryptographic properties of the chaotic maps such as sensitivity to initial conditions and random-like behavior have attracted the attention of cryptographers to develop new encryption algorithms. Therefore, recent researches of image encryption algorithms have been increasingly based on chaotic systems, though the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper proposes a Coupled Nonlinear Chaotic Map, called CNCM, and a novel chaos-based image encryption algorithm to encrypt color images by using CNCM. The chaotic cryptography technique which used in this paper is a symmetric key cryptography with a stream cipher structure. In order to increase the security of the proposed algorithm, 240 bit-long secret key is used to generate the initial conditions and parameters of the chaotic map by making some algebraic transformations to the key. These transformations as well as the nonlinearity and coupling structure of the CNCM have enhanced the cryptosystem security. For getting higher security and higher complexity, the current paper employs the image size and color components to cryptosystem, thereby significantly increasing the resistance to known/chosen-plaintext attacks. The results of several experimental, statistical analysis and key sensitivity tests show that the proposed image encryption scheme provides an efficient and secure way for real-time image encryption and transmission.

In this paper, the problem of robust stability for uncertain linear neutral systems with discrete and distributed delays is considered. The uncertainties under consideration are norm bounded, and possibly time varying. Some novel delay-dependent stability criteria are derived and formulated in the form of a linear matrix inequalities (LMIs) by a new class of Lyapunov–Krasovskii functionals which is constructed based on the descriptor model of the system and the method of decomposition. The new criteria are less conservative than the existing ones. Numerical examples illustrate that the proposed criteria are effective and achieve significant improvement over the results proposed in previous paper.

Remarkably benign looking logistic transformations x n +1 = r x n (1 − x n ) for choosing x 0 between 0 and 1 and 0 r ⩽ 4 have found a celebrated place in chaos, fractals and discrete dynamics. The strong physical meaning of Mandelbrot and Julia sets is broadly accepted and nicely connected by Christian Beck [Beck C. Physical meaning for Mandelbrot and Julia sets. Physica D 1999;125(3–4):171–182. Zbl0988.37060] to the complex logistic maps, in the former case, and to the inverse complex logistic map, in the latter case. The purpose of this paper is to study the bounded behavior of the complex logistic map using superior iterates and generate fractals from the same. The analysis in this paper shows that many beautiful properties of the logistic map are extendable for a larger value of r .

Evolutionary Algorithms (EAs) are stochastic and robust meta-heuristics of evolutionary computation field useful to solve optimization problems in image processing applications. Recently, as special mechanism to avoid being trapped in local minimum, the ergodicity property of chaotic sequences has been used in various designs of EAs. Three differential evolution approaches based on chaotic sequences using logistic equation for image enhancement process are proposed in this paper. Differential evolution is a simple yet powerful evolutionary optimization algorithm that has been successfully used in solving continuous problems. The proposed chaotic differential evolution schemes have fast convergence rate but also maintain the diversity of the population so as to escape from local optima. In this paper, the image contrast enhancement is approached as a constrained nonlinear optimization problem. The objective of the proposed chaotic differential evolution schemes is to maximize the fitness criterion in order to enhance the contrast and detail in the image by adapting the parameters using a contrast enhancement technique. The proposed chaotic differential evolution schemes are compared with classical differential evolution to two testing images. Simulation results on three images show that the application of chaotic sequences instead of random sequences is a possible strategy to improve the performance of classical differential evolution optimization algorithm.

In this paper, we transmute the solution for a new system of linear variational inequalities to an equilibrium point of neural networks, and by using analytic technique, some sufficient conditions are presented. Further, the estimation of the exponential convergence rates of the neural networks is investigated. The new and useful results obtained in this paper generalize and improve the corresponding results of recent works.

Quadratic programming has been widely applied to solving real-world problems. Recently, Liu describes a solution method for solving a class of fuzzy quadratic programming problems, where the cost coefficients of the linear terms in objective function, constraint coefficients, and right-hand sides are fuzzy numbers [Liu ST. Quadratic programming with fuzzy parameters: a membership function approach. Chaos, Solitons & Fractals 2009;40:237–45]. In this paper, we generalize Liu’s method to a more general fuzzy quadratic programming problem, where the cost coefficients in objective function, constraint coefficients, and right-hand sides are all fuzzy numbers. A pair of two-level mathematical programs is formulated to calculate the upper bound and lower bound of the objective values of the fuzzy quadratic program. Based on the duality theorem and by applying the variable transformation technique, the pair of two-level mathematical programs is transformed into a family of conventional one-level quadratic programs. Solving the pair of quadratic programs produces the fuzzy objective values of the problem. With the ability of calculating the fuzzy objective value developed in this paper, it might help initiate wider applications.

Fractals in nature are always a result of some growth process. The language of fractals which has been created specifically for the description of natural growth process is called L-systems. Recently, superior iterations (essentially, investigated by Mann [Mann WR. Mean value methods in iteration. Proc Am Math Soc 1953;4:506–10 [MR0054846 (14,988f)]]) has been introduced in the study of fractal and chaos. In this paper, inspired by superior iterates, we have generated fractal plants categorically using stochastic L-system. Some beautiful plants are also given in the paper.

Period-doubling bifurcation and its route to chaos have been thoroughly investigated in voltage-mode and current-mode controlled DC motor drives under simple proportional control. In this paper, the phenomena of Hopf bifurcation and chaos from torus breakdown in a voltage-mode controlled DC drive system is reported. It has been shown that Hopf bifurcation may occur when the DC drive system adopts a more practical proportional-integral control. The phenomena of period-adding and phase-locking are also observed after the Hopf bifurcation. Furthermore, it is shown that the stable torus can breakdown and chaos emerges afterwards. The work presented in this paper provides more complete information about the dynamical behaviors of DC drive systems.

This paper illustrates an approach to generate multi-wing attractors in coupled Lorenz systems. In particular, novel four-wing (eight-wing) hyperchaotic attractors are generated by coupling two (three) identical Lorenz systems. The paper shows that the equilibria of the proposed systems have certain symmetries with respect to specific coordinate planes and the eigenvalues of the associated Jacobian matrices exhibit the property of similarity. In analogy with the original Lorenz system, where the two-wings of the butterfly attractor are located around the two equilibria with the unstable pair of complex-conjugate eigenvalues, this paper shows that the four-wings (eight-wings) of these attractors are located around the four (eight) equilibria with two (three) pairs of unstable complex-conjugate eigenvalues.

In a recent paper [Soleimani-damaneh M. Fuzzy upper bounds and their applications. Chaos, Solitons & Fractals 2008;36:217–25.], I established the existence of a distance-based fuzzy upper bound for the objective function of a fuzzy DEA model, using the properties of a discussed signed distance, and provided an effective approach to solve that model. In this paper a new dual-based proof for the existence of the above-mentioned upper bound is provided which gives a useful insight into the theory of fuzzy DEA.

In this paper, several classes of impulsive Cohen–Grossberg neural networks with continuously distributed delays are considered. Global exponential stability and robust global exponential stability of the equilibrium solution are investigated by using Lyapunov function and integro-differential inequality. Moreover, sufficient conditions are also given to guarantee the existence of ϖ-periodic solution and that all other solutions are convergent to it globally exponentially. Finally, two examples are given to demonstrate the effectiveness of our results in this paper.

This paper proposes a novel particle swarm optimization (PSO) algorithm, chaotically encoded particle swarm optimization algorithm (CENPSOA), based on the notion of chaos numbers that have been recently proposed for a novel meaning to numbers. In this paper, various chaos arithmetic and evaluation measures that can be used in CENPSOA have been described. Furthermore, CENPSOA has been designed to be effectively utilized in data mining applications.

Since the investigation of impulsive delay differential equations is beginning, the literature on delay epidemic models with pulse vaccination is not extensive. In this paper, we propose a new SEIRS epidemic disease model with two profitless delays and vertical transmission, and analyze the dynamics behaviors of the model under pulse vaccination. Using the discrete dynamical system determined by the stroboscopic map, we obtain a ‘infection-free’ periodic solution, further, show that the ‘infection-free’ periodic solution is globally attractive when some parameters of the model are under appropriate conditions. Using a new modeling method, we obtain sufficient condition for the permanence of the epidemic model with pulse vaccination. We show that time delays, pulse vaccination and vertical transmission can bring different effects on the dynamics behaviors of the model by numerical analysis. Our results also show the delays are “profitless”. In this paper, the main feature is to introduce two discrete time delays, vertical transmission and impulse into SEIRS epidemic model and to give pulse vaccination strategies.

In this paper, the anti-synchronization of a general class of chaotic systems is investigated. A simple adaptive feedback scheme is proposed to anti-synchronize many familiar chaotic systems, including autonomous systems and non-autonomous systems. Lyapunov analysis for the error system gives the asymptotic stability conditions based on the invariance principle of differential equations. The schemes are successfully applied to three groups of examples: the van der Pol–Duffing oscillator, the parametrically harmonically excited 4D system, and the additionally harmonically excited Murali–Lakshmanan–Chua circuit. Numerical results are presented to justify the theoretical analysis in this paper.

Let k: be a field and q a nonzero element in k such that the square roots of q are in k. We use Hq to denote an affine Hecke algebra over k of type with parameter q. The purpose of this paper is to study representations of Hq by using based rings of two-sided cells of an affine Weyl group W of type . We shall give the classification of irreducible representations of Hq. We also remark that a calculation in [11] actually shows that Theorem 2 in [1] needs a modification, a fact is known to Grojnowski and Tanisaki long time ago. In this paper we also show an interesting relation between Hq and an Hecke algebra corresponding to a certain Coxeter group. Apparently the idea in this paper works for all affine Weyl groups, but that is the theme of another paper.

In this paper, the problem of robust exponential stability for a class of interval Cohen–Grossberg neural networks with time-varying delays is investigated. Without assuming the boundedness and differentiability of the activation functions and any symmetry of interconnection matrices, some sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point are derived. Some comparisons between the results presented in this paper and the previous results admit that our results are the improvement and extension of the existed ones. The validity and performance of the new results are further illustrated by two simulation examples.

Starting from the delay Lienard and van der Pol equations with time delay, this paper represents an attempt to give an introductory presentation of dynamics for a class of nonlinear systems with time delay and emphasizes the recent development on this field in china. It is clearly seen that the time delay occurred in systems can lead to the rich dynamical behaviors such as death island, Hopf bifurcation, double Hopf bifurcation, period-doubling bifurcation, phase locked (periodic) and phase shifting solutions, co-existing motions, quasi-periodic motion and even chaos. In the quantitative and qualitative treatment of the analytical method, a new method, called perturbation-incremental scheme (PIS), is introduced by two steps, namely perturbation and increment for continuation to the critical value at a simple Hopf bifurcation. This paper shows that time delay may be used as a simple but efficient “switch” to control motions of a system: either from order to complex motions or from complex to order motions for different applications. As well as the PIS can bypass and avoid the tedious calculation of the center manifold reduction (CMR) and normal form.

Chaotic cryptology has been widely investigated recently. A common feature in the most recent developments of chaotic cryptosystems is the use of a single dynamical rule in the encoding–decoding process. The main objective of this paper is to provide a set of chaotic systems instead of a single one for cryptography. In this paper, we introduce a chaotic cryptosystem based on the symbolic dynamics of random maps with position dependent weighting probabilities. The random maps model is a deterministic dynamical system in a finite phase space with n points. The maps that establish the dynamics of the system are chosen randomly for every point. The essential idea of this paper is that, given two dynamical systems that behave in a certain way, it is possible to combine them (by composing) into a new dynamical system. This dynamically composed system behaves in a completely different way compared to the constituent systems. The proposed scheme exploits the symbolic dynamics of a set of chaotic maps in order to encode the binary information. The performance of the new cryptosystem based on chaotic dynamical systems properties is examined. Both theoretical and experimental results demonstrate that the proposed algorithm using symbolic dynamics achieves the optimal security criteria.

Comprehensive numerical simulations (reviewed in Dissipative Solitons, Akhmediev and Ankiewicz (Eds.), Springer, Berlin, 2005) of pulse solutions of the cubic–quintic Ginzburg–Landau Equation (CGLE), a canonical equation governing the weakly nonlinear behavior of dissipative systems in a wide variety of disciplines, reveal various intriguing and entirely novel classes of solutions. In particular, there are five new classes of pulse or solitary waves solutions, viz. pulsating, creeping, snake, erupting, and chaotic solitons. In contrast to the regular solitary waves investigated in numerous integrable and non-integrable systems over the last three decades, these dissipative solitons are not stationary in time. Rather, they are spatially confined pulse-type structures whose envelopes exhibit complicated temporal dynamics. The numerical simulations also reveal very interesting bifurcations sequences of these pulses as the parameters of the CGLE are varied. In this paper, we address the issues of central interest in the area, i.e., the conditions for the occurrence of the five categories of dissipative solitons, as well the dependence of both their shape and their stability on the various parameters of the CGLE, viz. the nonlinearity, dispersion, linear and nonlinear gain, loss and spectral filtering parameters. Our predictions on the variation of the soliton amplitudes, widths and periods with the CGLE parameters agree with simulation results. First, we elucidate the Hopf bifurcation mechanism responsible for the various pulsating solitary waves, as well as its absence in Hamiltonian and integrable systems where such structures are absent. Next, we develop and discuss a variational formalism within which to explore the various classes of dissipative solitons. Given the complex dynamics of the various dissipative solutions, this formulation is, of necessity, significantly generalized over all earlier approaches in several crucial ways. Firstly, the starting formulation for the Lagrangian is recent and not well explored. Also, the trial functions have been generalized considerably over conventional ones to keep the shape relatively simple (and the trial function integrable!) while allowing arbitrary temporal variation of the amplitude, width, position, speed and phase of the pulses. In addition, the resulting Euler–Lagrange equations are treated in a completely novel way. Rather than consider the stable fixed points which correspond to the well-known stationary solitons or plain pulses, we use dynamical systems theory to focus on more complex attractors viz. periodic, quasiperiodic, and chaotic ones. Periodic evolution of the trial function parameters on stable periodic attractors yield solitons whose amplitudes and widths are non-stationary or time dependent. In particular, pulsating and snake dissipative solitons may be treated in this manner. Detailed results are presented here for the pulsating solitary waves – their regimes of occurrence, bifurcations, and the parameter dependences of the amplitudes, widths, and periods agree with simulation results. Snakes and chaotic solitons will be addressed in subsequent papers. This overall approach fails only to address the fifth class of dissipative solitons, viz. the exploding or erupting solitons.

This paper considers the global output convergence of Cohen–Grossberg neural networks with both time-varying and distributed delays. The inputs of the neural networks are required to be time-varying and the activation functions should be globally Lipschitz continuous and monotonely nondecreasing. Based on M-matrix theory, several sufficient conditions are established to guarantee the global output convergence of this class of neural networks. Symmetry in the connection weight matrices and the boundedness of the activation functions are abandoned in this paper. The convergence results are useful in solving some optimization problems and the design of Cohen–Grossberg neural networks with both time-varying and distributed delays. Two examples are given to illustrate the effectiveness of our results.

This paper deals with the observer-based synchronization in a cascade connection of hyperchaotic discrete-time systems. The paper demonstrates that exact synchronization in finite time is achievable between pairs of drive–response systems using only a scalar synchronizing signal. This “propagated synchronization” starts from the innermost drive–response system pair and propagates toward the outermost drive-system pair. Choosing the drive-system input to be an information signal (encrypted via an arbitrary encryption function) yields a potential application of this architecture in chaos-based communications.

In this paper, the stability of neural networks with both variable and unbounded delays is investigated. With simpler assumption that the activation functions are continuous and monotone non-decreasing, we employ homeomorphism techniques and Lyapunov functional to establish some sufficient conditions ensuring the global asymptotic stability and exponential stability of equilibrium of neural networks with both variable and unbounded delays. The new and useful results obtained in this paper extend and improve the existing ones in the previous literature.

In this paper, complex dynamical behavior of a class of centrifugal flywheel governor system is studied. These systems have a rich variety of nonlinear behavior, which are investigated here by numerically integrating the Lagrangian equations of motion. A tiny change in parameters can lead to an enormous difference in the long-term behavior of the system. Bubbles of periodic orbits may also occur within the bifurcation sequence. Hyperchaotic behavior is also observed in cases where two of the Lyapunov exponents are positive, one is zero, and one is negative. The routes to chaos are analyzed using Poincare maps, which are found to be more complicated than those of nonlinear rotational machines. Periodic and chaotic motions can be clearly distinguished by all of the analytical tools applied here, namely Poincare sections, bifurcation diagrams, Lyapunov exponents, and Lyapunov dimensions. This paper proposes a parametric open-plus-closed-loop approach to controlling chaos, which is capable of switching from chaotic motion to any desired periodic orbit. The theoretical work and numerical simulations of this paper can be extended to other systems. Finally, the results of this paper are of practical utility to designers of rotational machines.

In this paper, an efficient modification of the Adomian decomposition method by using Legendre polynomials is presented. Both linear and non-linear models are suited for the proposed method. Some examples here in are solved by using this method and this paper will demonstrate that the results are more reliable and efficient.

To estimate the ultimate bound and positively invariant set for a dynamic system is an important but quite challenging task in general. In this paper, we attempt to investigate the ultimate bound and positively invariant set for the hyperchaotic Lorenz–Haken system using a technique combining the generalized Lyapunov function theory and optimization. For the Lorenz–Haken system, we derive a four-dimensional ellipsoidal ultimate bound and positively invariant set. Furthermore, the two-dimensional parabolic ultimate bound with respect to x–z is established. Finally, numerical results to estimate the ultimate bound are also presented for verification. The results obtained in this paper are important and useful in control, synchronization of hyperchaos and their applications.

In this paper, we have studied the plasmatic membrane behavior using an electric circuit developed by Hodgkin and Huxley in 1952 and have dealt with the variation of the amount of time related to the potassium and sodium conductances in the squid axon. They developed differential equations for the propagation of electric signals; the dynamics of the Hodgkin–Huxley model have been extensively studied both from the view point of its their biological implications and as a test bed for numerical methods, which can be applied to more complex models. Recently, an irregular chaotic movement of the action potential of the membrane was observed for a number of techniques of control with the objective to stabilize the variation of this potential. This paper analyzes the non-linear dynamics of the Hodgkin–Huxley mathematical model, and we present some modifications in the governing equations of the system in order to make it a non-ideal one (taking into account that the energy source has a limited power supply). We also developed an optimal linear control design for the action potential of membranes. Here, we discuss the conditions that allow the use of control linear feedback for this kind of non-linear system.

This paper investigates the nonlinear response and bifurcation of rotor with Squeezed Film Damper (SFD) supported on elastic foundation. The motion equations are derived. To analyze the bifurcation of nonlinear response of SFD rotor, the Floquet Multipliers is obtained by solving the perturbation equations with numerical method. For computing Floquet Multipliers, a novel method is presented in this paper, which can begin integration at the stable solution. Simulation results are given in two figures. One figure, which consists of eight subfigures, gives the effect of rotating speed on the response of SFD damper supported on elastic foundation: with increasing rotating speed, the nonlinear response evolves from quasi-period to period, then jumps between different periods, and finally returns to quasi-period; the corresponding bifurcations are saddle-node bifurcation and secondary Hopf bifurcation. The second figure, which consists of six subfigures, shows that: the support stiffness has large influence on the response of bearings and film force in SFD; large support stiffness can lead to oil whirl in SFD.

The equation hierarchy presented in this paper contains the KdV equation and the mKdV equation. By use of the concept of characteristic number, an undetermined-constant method is proposed by us, for which the polynomial Hamiltonian functions are constructed. By employing the method, the Hamiltonian structure of the equation hierarchy is established. The approach presented in the paper shares extensive applications. In addition, four explicit expressions of the travelling wave solutions to the above equation hierarchy are obtained. One of them is regular, the other three are singular.

R/S method is widely used to estimate long-range dependence of a time series, but few papers do research on how to use the R/S method to determine the periodicity. In this paper, the log ( h ) - log ( ( R / S ) h ) figures and the log ( h ) - V h figures are further studied by lots of numeral simulations, which shows that the two figures of a periodic time series both have obviously similar structures. Based on these structures, a new method, similar figure method (SFM), is established to estimate whether a time series has periodicity and determine the length of the periodicity. SFM is tested with a disturbed nonlinear time series, an actual monthly runoff series and a random series. The results show that SFM is effective. This method is an extension to the R/S analysis.

In this paper, a Z3-equivariant quartic planar vector field is studied. The Hopf bifurcation method and polycycle bifurcation method are combined to study the limit cycles bifurcated from the polycycle with three hyperbolic saddle points. It is found that this special quartic planar polynomial system has at least three large limit cycles which surround 13 singular points. By applying the double homoclinic loops bifurcation method and Poincare–Bendixson theorem, we conclude that 16 limit cycles with two different configurations exist in this special planar polynomial system. The results acquired in this paper are useful to the study of the second part of 16th Hilbert Problem.

This paper investigates asymptotic stability problem for neutral system with interval time-varying delays and two classes of uncertainties. Delay-dependent and delay-independent criteria are proposed to guarantee the asymptotic stability for our considered systems. Lyapunov–Krasovskii functional and Leibniz–Newton formula are applied to find the delay-dependent stability results. Linear matrix inequality (LMI) approach is used to solve the proposed conditions. Finally, some numerical examples are illustrated to show the improvement of this paper.

In a recent paper [Melby P, Kaidel J, Weber N, Hubler A. Adaptation to the edge of chaos in the self-adjusting logistic map. Phys Rev Lett 2000;84:5991–3], Melby et al. attempted to understand edge of chaos behaviour through a very simple model. Based on our exhaustive numerical experiments, here we show that the model, with the definition of the edge of chaos given in the paper, cannot unequivocally support the idea of adaptation to the edge of chaos, let alone allow a conjecture of its generic presence in systems having the same characteristic features.

In this paper, some sufficient conditions are obtained for checking the existence and exponential stability of almost periodic solution for bidirectional associative memory Hopfield-type neural networks with impulse. The approaches are based on contraction principle and Gronwall–Bellman’s inequality. This paper is considering the almost periodic solution for impulsive Hopfield-type neural networks.

In this paper the problem of chaos control in nonlinear maps using minimization of entropy function is investigated. Invariant probability measure of a chaotic dynamics can be used to produce an entropy function in the sense of Shannon. In this paper it is shown that how the entropy control technique is utilized for chaos elimination. Using only the measured states of a chaotic map the probability measure of the system is numerically estimated and this estimated measure is used to obtain an estimation for the entropy of the chaotic map. The control variable of the chaotic system is determined in such a way that the entropy function descends until the chaotic trajectory of the map is replaced with a regular one. The proposed idea is applied for stabilizing the fixed points of the logistic and the Henon maps as some cases of study. Simulation results show the effectiveness of the method in chaos rejection when only the statistical information is available from the under-study systems.

In this paper by using a combination of fuzzy identification and the sliding mode control a fuzzy adaptive sliding mode scheme is designed to stabilize the unstable periodic orbits of chaotic systems. The chaotic system is assumed to have an affine form x(n) = f(X) + g(X)u where f and g are unknown functions. Using only the input–output data obtained from the underlying dynamical system, two fuzzy systems are constructed for identification of f and g. Two distinct methods are utilized for fuzzy modeling, the least squares and the gradient descent techniques. Based on the estimated fuzzy models, an adaptive controller, which works through the sliding mode control, is designed to make the system track the desired unstable periodic orbits. The stability analysis of the overall closed loop system is presented in the paper and the effectiveness of the proposed adaptive scheme is numerically investigated. As a case of study, modified Duffing system is selected for applying the proposed method to stabilize its 2π and 4π periodic orbits. Simulation results show the high performance of the method for stabilizing the unstable periodic orbits of unknown chaotic systems.

This paper deals with the problem of robust stability for uncertain neural networks with time-varying delays. The system possesses time-varying and norm-bounded uncertainties. The time-varying delay function in this paper is not required to be either continuously differentiable, or its derivative less than one. Based on Lyapunov–Krasovskii functional approach, new delay-dependent and delay-derivative-dependent stability criteria are presented, which are given in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the effectiveness and less conservativeness of the developed techniques.

Controlling chaos and chaotification using delayed continuous feedback is studied in this paper. The effects of time delay parameters on the dynamics of the Chen–Lee system were numerically studied. The system displays comprehensive dynamic behaviors, such as fixed points, periodic motion, and chaotic motion. The maximum Lyapunov exponent, time histories, and phase trajectories all indicated that chaotic motion could successfully be controlled. Period doubling routes to chaos and inverse period doubling phenomena were also found in the Chen–Lee system. This paper points out that the time delay parameters are good switch keys. The dynamics of this system can be controlled under appropriate feedback gains and delay times. This study showed that the delayed control feedback (DCF) method is very straightforward, and that it is easy to switch from a chaotic trajectory to a regular periodic orbit while simultaneously improving the system’s properties.

In this paper, the global exponential periodicity and stability of recurrent neural networks with time-varying delays are investigated by applying the idea of vector Lyapunov function, M-matrix theory and inequality technique. We assume neither the global Lipschitz conditions on these activation functions nor the differentiability on these time-varying delays, which were needed in other papers. Several novel criteria are found to ascertain the existence, uniqueness and global exponential stability of periodic solution for recurrent neural network with time-varying delays. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. Some previous results are improved and generalized, and an example is given to show the effectiveness of our method.

A few reduced equations from the self-dual Yang–Mills equations are presented, which are seemly extended zero curvature equations. As their applications, a good many nonlinear evolution equations could be obtained. In this paper, a (2 + 1)-dimensional AKNS hierarchy of soliton equations is generated from one of reduced equations of the self-dual Yang–Mills equations. With the help of a proper loop algebra, the Hamiltonian structure of its expanding integrable model (actually, its integrable couplings) is worked out by using the quadratic-form identity, which is Liouville integrable. The way presented in the paper has extensive applications. That is to say, making use of the approach specially a few higher-dimensional zero curvature equations in the paper could produce a lots of higher-dimensional integrable coupling systems and their corresponding Hamiltonian structures.

High-order neural networks can be considered as an expansion of Hopfield neural networks, and have stronger approximation property, faster convergence rate, greater storage capacity, and higher fault tolerance than lower-order neural networks. In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with discrete and distributed time-delays. Based on an Lyapunov–Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived, which guarantee the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the stochastic high-order delayed neural networks under consideration are globally asymptotically stable in the mean square if two linear matrix inequalities (LMIs) are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also shown that the main results in this paper cover some recently published works. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria.