Catálogo de publicaciones - revistas

<jats:p>To date, there are very few studies on the transition beyond second Hopf bifurcation in a lid–driven square cavity, due to the difficulties in theoretical analysis and numerical simulations. In this paper, we study the characteristics of the third Hopf bifurcation in a driven square cavity by applying a consistent fourth-order compact finite difference scheme rectently developed by us. We numerically identify the critical Reynolds number of the third Hopf bifurcation located in the interval of (13944.7021,13946.5333) by the method of bisection. Through Fourier analysis, it is discovered that the flow becomes chaotic with a characteristic of period-doubling bifurcation when the Reynolds number is beyond the third bifurcation critical interval. Nonlinear time series analysis further ascertains the flow chaotic behaviors via the phase diagram, Kolmogorov entropy and maximal Lyapunov exponent. The phase diagram changes interestingly from a closed curve with self-intersection to an unclosed curve and the attractor eventually becomes strange when the flow becomes chaotic.</jats:p>

<jats:p>Hydro-turbine governing system is a time-varying complex system with strong non-linearity, and its dynamic characteristics are jointly affected by hydraulic, mechanical, electrical, and other factors. Aiming at the stability of the hydro-turbine governing system, this paper first builds a dynamic model of the hydro-turbine governing system through mechanism modeling, and introduces the transfer coefficient characteristics under different load conditions to obtain the stability category of the system. BP neural network is used to perform the machine study and the predictive analysis of the stability of the system under different working conditions is carried out by using the additional momentum method to optimize the algorithm. The test set results show that the method can accurately distinguish the stability category of the hydro-turbine governing system (HTGS), and the research results can provide a theoretical reference for the operation and management of smart hydropower stations in the future.</jats:p>

<jats:p>When a phototube is activated to connect a neural circuit, the output voltage becomes sensitive to external illumination because the photocurrent across the phototube can be controlled by external electromagnetic wave. The channel currents from different branch circuits have different impacts on the outputs voltage of the neural circuit. In this paper, a phototube is incorporated into different branch circuits in a simple neural circuit, and then a light-controlled neuron is obtained for further nonlinear analysis. Indeed, the phototube is considered as exciting source when it is activated by external illumination, and two kinds of light-sensitive neurons are obtained when the phototube is connected to capacitor or induction coil, respectively. Electric synapse coupling is applied to detect possible synchronization between two functional neurons, and the energy consumption along the coupling channel via resistor is estimated. The analog circuits for the two kinds of light-sensitive neurons are supplied for further confirmation by using Multisim. It is found that two light-sensitive neurons and neural circuits can be synchronized by taming the coupling intensity carefully. It provides possible clues to understand the synchronization mechanism for eyes and artificial sensors which are sensitive to illumination. Finally, a section for open problems is supplied for further investigation about its collective behaviors in the network with/without synapse coupling.</jats:p>

<jats:p>A simple variable-boostable system is selected as the structure for hosting an arbitrarily defined memristor for chaos producing. The derived three-dimensional (3-D) memristive chaotic system shows its distinct property of offset, amplitude and frequency control. Owing its merits any desired number of coexisting attractors are embedded by means of attractor doubling and self-reproducing based on function-oriented offset boosting. In this circumstance two classes of control gates are found: one determines the number of coexisting attractors resorting to the independent offset controller whil the other is the initial condition selecting any one of them. Circuit simulation gives a consistent output with theoretically predicted embedded attractors.</jats:p>

<jats:p>A fractional-order difference equation model of a third-order discrete phase-locked loop (FODPLL) is discussed and the dynamical behavior of the model is demonstrated using bifurcation plots and a basin of attraction. We show a narrow region of loop gain where the FODPLL exhibits quasi-periodic oscillations, which were not identified in the integer-order model. We propose a simple impulse control algorithm to suppress chaos and discuss the effect of the control step. A network of FODPLL oscillators is constructed and investigated for synchronization behavior. We show the existence of chimera states while transiting from an asynchronous to a synchronous state. The same impulse control method is applied to a lattice array of FODPLL, and the chimera states are then synchronized using the impulse control algorithm. We show that the lower control steps can achieve better control over the higher control steps.</jats:p>

<jats:p>The sensitivity to fault reflection is very important for larger dynamic range in fiber fault detection technique. Using time delay signature (TDS) of chaotic laser formed by optical feedback can solve the sensitivity limitation of photodetector in fiber fault detection. The TDS corresponds to the feedback position and the fault reflection can be detected by the laser diode. The sensitivity to feedback level of circular-side hexagonal resonator (CSHR) microcavity laser is numerically simulated and the feedback level boundaries of each output dynamic state are demonstrated. The peak level of TDS is utilized to analyze the sensitivity. The demonstration is presented in two aspects: the minimum feedback level when the TDS emerges and the variation degree of TDS level on feedback level changing. The results show that the CSHR microcavity laser can respond to the feedback level of 0.07%, corresponding to -63-dB feedback strength. Compared to conventional distributed feedback laser, the sensitivity improves almost 20 dB due to the shorter internal cavity length of CSHR microcavity laser. Moreover, 1% feedback level changing will induce 1.001 variation on TDS level, and this variation degree can be influenced by other critical internal parameters (active region side length, damping rate, and linewidth enhancement factor).</jats:p>

<jats:p>Continuous-time memristor (CM) has been widely used to generate chaotic oscillations. However, discrete memristor (DM) has not been received adequate attention. Motivated by the cascade structure in electronic circuits, this paper introduces a method to cascade discrete memristive maps for generating chaos and hyperchaos. For a discrete-memristor seed map, it can be self-cascaded many times to get more parameters and complex structures, but with larger chaotic areas and Lyapunov exponents. Comparisons of dynamic characteristics between the seed map and cascading maps are explored. Meanwhile, numerical simulation results are verified by the hardware implementation.</jats:p>

<jats:p>This paper proposes a fractional-order simplest chaotic system using a bi-stable locally-active memristor. The characteristics of the memristor and transient transition behaviors of the proposed system are analyzed, and this circuit is implemented digitally using ARM-based MCU. Firstly, the mathematical model of the memristor is designed, which is nonvolatile, locally-activeand bi-stable. Secondly, the asymptotical stability of the fractional-order memristive chaotic system is investigated and some sufficient conditions of the stability are obtained. Thirdly, complex dynamics of the novel system are analyzed using phase diagram, Lyapunov exponential spectrum, bifurcation diagram, basin of attractor, and coexisting bifurcation, coexisting attractors are observed. All of these results indicate that this simple system contains the abundant dynamic characteristics. Moreover, transient transition behaviors of the system are analyzed, and it is found that the behaviors of transient chaotic and transient period transition alternately occur. Finally, the hardware implementation of the fractional-order bi-stable locally-active memristive chaotic system using ARM-based STM32F750 is carried out to verify the numerical simulation results.</jats:p>

<jats:p>The firing of a neuron model is mainly affected by the following factors: the magnetic field, external forcing current, time delay, <jats:italic>etc</jats:italic>. In this paper, a new time-delayed electromagnetic field coupled dual Hindmarsh – Rose neuron network model is constructed. A magnetically controlled threshold memristor is improved to represent the self-connected and the coupled magnetic fields triggered by the dynamic change of neuronal membrane potential for the adjacent neurons. Numerical simulation confirms that the coupled magnetic field can activate resting neurons to generate rich firing patterns, such as spiking firings, bursting firings, and chaotic firings, and enable neurons to generate larger firing amplitudes. The study also found that the strength of magnetic coupling in the neural network also affects the number of peaks in thedischarge of bursting firing. Based on the existing medical treatment background of mental illness, the effects of time lag in the coupling process against neuron firing are studied. The results confirm that the neurons can respond well to external stimuli and coupled magnetic field with appropriate time delay, and keep periodic firing under a wide range of external forcing current.</jats:p>

<jats:p>Recent studies in complexity science have uncovered temporal regularities in the dynamics of impact along scientific and other creative careers, but they did not extend the obtained insights to firms. In this paper, we show that firms’ technological impact patterns cannot be captured by the state-of-the-art dynamical models for the evolution of scientists’ research impact, such as the <jats:italic>Q</jats:italic> model. Therefore, we propose a time-varying returns model which integrates the empirically-observed relation between patent order and technological impact into the <jats:italic>Q</jats:italic> model. The proposed model can reproduce the timing pattern of firms’ highest-impact patents accurately. Our results shed light on modeling the differences behind the impact dynamics of researchers and firms.</jats:p>