Multiple mixed state variable incremental integration for reconstructing extreme multistability in a novel memristive hyperchaotic jerk system with multiple cubic nonlinearity

Memristor-based chaotic systems with infinite equilibria are interesting because they generate extreme multistability.Their initial state-dependent dynamics can be explained in a reduced-dimension model by converting the incremental integration of the state variables into system parameters.However,this approach cannot solve memristive systems in the presence of nonlinear terms other than the memristor term.In addition,the converted state variables may suffer from a degree of divergence.To allow simpler mechanistic analysis and physical implementation of extreme multistability phenomena,this paper uses a multiple mixed state variable incremental integration(MMSVII)method,which successfully reconstructs a four-dimensional hyperchaotic jerk system with multiple cubic nonlinearities except for the memristor term in a three-dimensional model using a clever linear state variable mapping that eliminates the divergence of the state variables.Finally,the simulation circuit of the reduced-dimension system is constructed using Multisim simulation software and the simulation results are consistent with the MATLAB numerical simulation results.The results show that the method of MMSVII proposed in this paper is useful for analyzing extreme multistable systems with multiple higher-order nonlinear terms.

Control method based on DRFNN sliding mode for multifunctional flexible multistate switch

To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this study.This approach is based on an improved double-loop recursive fuzzy neural network(DRFNN)sliding mode,which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults.First,an improved DRFNN sliding mode control(SMC)method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system.To improve the robustness of the system,an adaptive parameter-adjustment strategy for the DRFNN is designed,where its dynamic mapping capabilities are leveraged to improve the transient compensation control.Additionally,a quasi-continuous second-order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability.The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem.A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink.The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.

Minimization of the Expected Total Net Loss in a Stationary Multistate Flow Network System

In the present paper, a three-component, stationary, multistate flow network system is studied. Detailed costs and incomes are specified. The aim is to minimize the expected total net loss with respect to the expected times the components spend in each state. This represents a novelty in that we connect the expected component times spent in each state to the minimal total net loss of the system, without first finding the component importance. This is of interest in the design phase where one may tune the components to minimize the expected total net loss. Due to the complex nature of the problem, we first study a simplified version. There the expected times spent in each state are assumed equal for each component. Then a modified version of the full model is presented. The optimization in this model is completed in two steps. First the optimization is carried out for a set of pre-chosen fixed expected life cycle lengths. Then the overall minimum is identified by varying these expectations. Both the simplified and the modified optimization problems are nonlinear. The setup used in this article is such that it can easily be modified to represent other flow network systems and cost functions. The challenge lies in the optimization of real life systems.

Optimization of Critical Systems for Robustness in a Multistate World

Critical systems are typically complex systems that are required to perform reliably over a wide range of scenarios, or multistate world. Seldom does a single system exist that performs best for all plausible scenarios. A robust solution, one that performs relatively well over a wide range of scenarios, is often the preferred choice for reduced risk at an acceptable cost. The alternative with the maximum expected utility may possess vulnerabilities that could be exploited. The best strategy is likely to be a hybrid solution. The von Neumann-Morgenstern Expected Utility Theory (EUT) would never select such a solution because, given its linear functional form, the expected utility of a hybrid solution cannot be greater than that of every constituent alternative. The continuity axiom and the independence axiom are assessed to be unrealistic for the problem of interest. Several well-known decision models are analyzed and demonstrated to be potentially misleading. The linear disappointment model modifies EUT by adding a term proportional to downside risk;however, it does not provide a mathematical basis for determining preferred hybrid solutions. The paper proposes a portfolio allocation model with stochastic optimization as a flexible and transparent method for defining choice problems and determining hybrid solutions for critical systems with desirable properties such as diversification and robustness.

Memristor hyperchaos in a generalized Kolmogorov-type system with extreme multistability

Memristor chaotic systems have aroused great attention in recent years with their potentials expected in engineering applications.In this paper,a five-dimension(5D)double-memristor hyperchaotic system(DMHS)is modeled by introducing two active magnetron memristor models into the Kolmogorov-type formula.The boundness condition of the proposed hyperchaotic system is proved.Coexisting bifurcation diagram and numerical verification explain the bistability.The rich dynamics of the system are demonstrated by the dynamic evolution map and the basin.The simulation results reveal the existence of transient hyperchaos and hidden extreme multistability in the presented DMHS.The NIST tests show that the generated signal sequence is highly random,which is feasible for encryption purposes.Furthermore,the system is implemented based on a FPGA experimental platform,which benefits the further applications of the proposed hyperchaos.

A novel variable-order fractional chaotic map and its dynamics

In recent years,fractional-order chaotic maps have been paid more attention in publications because of the memory effect.This paper presents a novel variable-order fractional sine map(VFSM)based on the discrete fractional calculus.Specially,the order is defined as an iterative function that incorporates the current state of the system.By analyzing phase diagrams,time sequences,bifurcations,Lyapunov exponents and fuzzy entropy complexity,the dynamics of the proposed map are investigated comparing with the constant-order fractional sine map.The results reveal that the variable order has a good effect on improving the chaotic performance,and it enlarges the range of available parameter values as well as reduces non-chaotic windows.Multiple coexisting attractors also enrich the dynamics of VFSM and prove its sensitivity to initial values.Moreover,the sequence generated by the proposed map passes the statistical test for pseudorandom number and shows strong robustness to parameter estimation,which proves the potential applications in the field of information security.

Optical bistability and multistability in a three-level △-type atomic system under the nonresonant condition

Under a nonresonant condition, we theoretically investigate hybrid absorptive-dispersive optical bistability and multistability behaviours in a three-level △-type system by using a microwave field to drive a hyperfine transition between two upper excited states inside a unidirectional ring cavity. We find that the optical bistability and multistability behaviours can be controlled by adjusting the intensity of the microwave field or the intensity of the coherent coupling field. Furthermore, our studies show an interesting phenomenon of the transition from the optical bistability to the optical multistability only by changing the negative detuning of the coupling field into the positive detuning of the coupling field.

Locating Error Considering Dimensional Errors Modeling for Multistation Manufacturing System

Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a multi-station system. Current approaches to error modeling for multistation machining process are not explicit enough for error control and ensuring final product quality. In this paper, a mathematic model to depict the part dimensional variation of the complex multistation manufacturing process is formulated. A linear state space dimensional error propagation equation is established through kinematics analysis of the influence of locating parameter variations and locating datum variations on dimensional errors, so the dimensional error accumulation and transformation within the multistation process are quantitatively described. A systematic procedure to build the model is presented, which enhances the way to determine the variation sources in complex machining systems. A simple two-dimensional example is used to illustrate the proposed procedures. Finally, an industrial case of multistation machining part in a manufacturing shop is given to testify the validation and practicability of the method. The proposed analytical model is essential to quality control and improvement for multistation systems in machining quality forecasting and design optimization.

Multistability and coexisting transient chaos in a simple memcapacitive system

The self-excited attractors and hidden attractors in a memcapacitive system which has three elements are studied in this paper.The critical parameter of stable and unstable states is calculated by identifying the eigenvalues of Jacobian matrix.Besides,complex dynamical behaviors are investigated in the system,such as coexisting attractors,hidden attractors,coexisting bifurcation modes,intermittent chaos,and multistability.From the theoretical analyses and numerical simulations,it is found that there are four different kinds of transient transition behaviors in the memcapacitive system.Finally,field programmable gate array(FPGA)is used to implement the proposed chaotic system.

Probability Prediction in Multistate Survival Models for Patients with Chronic Myeloid Leukaemia

In order to find an appropriate model suitable for a multistate survival experiment, 634 patients with chronic myeloid leukaemia (CML) were selected to illustrate the method of analysis. After transplantation, there were 4 possible situations for a patient: disease free, relapse but still alive, death before relapse, and death after relapse. The last 3 events were considered as treatment failure. The results showed that the risk of death before relapse was higher than that of the relapse, especially in the first year after transplantation with competing-risk method. The result of patients with relapse time less than 12 months was much poor by the Kaplan-Meier method. And the multistate survival models were developed, which were detailed and informative based on the analysis of competing risks and Kaplan-Meier analysis. With the multistate survival models, a further analysis on conditional probability was made for patients who were disease free and still alive at month 12 after transplantation. It was concluded that it was possible for an individual patient to predict the 4 possible probabilities at any time. Also the prognoses for relapse either death or not and death either before or after relapse may be given. Furthermore, the conditional probabilities for patients who were disease free and still alive in a given time after transplantation can be predicted.

Design and multistability analysis of five-value memristor-based chaotic system with hidden attractors

A five-value memristor model is proposed,it is proved that the model has a typical hysteresis loop by analyzing the relationship between voltage and current.Then,based on the classical Liu-Chen system,a new memristor-based fourdimensional(4D)chaotic system is designed by using the five-value memristor.The trajectory phase diagram,Poincare mapping,bifurcation diagram,and Lyapunov exponent spectrum are drawn by numerical simulation.It is found that,in addition to the general chaos characteristics,the system has some special phenomena,such as hidden homogenous multistabilities,hidden heterogeneous multistabilities,and hidden super-multistabilities.Finally,according to the dimensionless equation of the system,the circuit model of the system is built and simulated.The results are consistent with the numerical simulation results,which proves the physical realizability of the five-value memristor-based chaotic system proposed in this paper.

Determination of Scheduled Travel Time for a Fixed Transit Route Based on Multistate Model

In order to provide the guideline for bus drivers to adjust speed to minimize scheduled deviation,the method for setting bus scheduled travel time is proposed. Firstly,multistate model is introduced to fit historical travel time data and identify different service states. Based on the calibrated travel time distribution parameters,an optimization model is proposed,followed by a Monte Carlo( MC) simulation based genetic algorithm( GA)procedure to obtain the optimal scheduled time. A case study from a fixed bus route from Shenzhen is used to demonstrate the model applicability. The sensitivity analysis is conducted to study the effects of parameters setting on optimal slack time for each segment. The results show that multistate model fits travel time under peak hours better than Lognormal distribution,and the length of scheduled travel time basically reflects travel time reliability.

Nonlinear signal transduction network with multistate

Signal transduction is an important and basic mechanism to cell life activities.The stochastic state transition of receptor induces the release of signaling molecular,which triggers the state transition of other receptors.It constructs a nonlinear sigaling network,and leads to robust switchlike properties which are critical to biological function.Network architectures and state transitions of receptor affect the performance of this biological network.In this work,we perform a study of nonlinear signaling on biological polymorphic network by analyzing network dynamics of the Ca^(2+)-induced Ca^(2+)release(CICR)mechanism,where fast and slow processes are involved and the receptor has four conformational states.Three types of networks,Erdos–R´enyi(ER)network,Watts–Strogatz(WS)network,and BaraB´asi–Albert(BA)network,are considered with different parameters.The dynamics of the biological networks exhibit different patterns at different time scales.At short time scale,the second open state is essential to reproduce the quasi-bistable regime,which emerges at a critical strength of connection for all three states involved in the fast processes and disappears at another critical point.The pattern at short time scale is not sensitive to the network architecture.At long time scale,only monostable regime is observed,and difference of network architectures affects the results more seriously.Our finding identifies features of nonlinear signaling networks with multistate that may underlie their biological function.

Search for d-MPs without duplicates in two-terminal multistate networks based on MPs

The reliability evaluation of a multistate network is primarily based on d-minimal paths/cuts(d-MPs/d-MCs).However,being a nondeterminism polynomial hard(NP-hard)problem,searching for all d-MPs is a rather challenging task.In existing implicit enumeration algorithms based on minimal paths(MPs),duplicate d-MP candidates may be generated.An extra step is needed to locate and remove these duplicate d-MP candidates,which costs significant computational effort.This paper proposes an efficient method to prevent the generation of duplicate d-MP candidates for implicit enumeration algorithms for d-MPs.First,the mechanism of generating duplicate d-MP candidates in the implicit enumeration algorithms is discussed.Second,a direct and efficient avoiding-duplicates method is proposed.Third,an improved algorithm is developed,followed by complexity analysis and illustrative examples.Based on the computational experiments comparing with two existing algorithms,it is found that the proposed method can significantly improve the efficiency of generating d-MPs for a particular demand level d.

Enhancements of SDR-Based FPGA System for V2X-VLC Communications

This pilot study focuses on a real measurements and enhancements of a software defined radio-based system for vehicle-to everything visible light communication(SDR-V2X-VLC).The presented system is based on a novel adaptive optimization of the feed-forward software defined equalization(FFSDE)methods of the least mean squares(LMS),normalized LMS(NLMS)and QR decomposition-based recursive least squares(QR-RLS)algorithms.Individual parameters of adaptive equalizations are adjusted in real-time to reach the best possible results.Experiments were carried out on a conventional LED Octavia III taillight drafted directly from production line and universal software radio peripherals(USRP)from National Instruments.The transmitting/receiving elements used multistate quadrature amplitude modulation(M-QAM)implemented in LabVIEW programming environment.Experimental results were verified based on bit error ratio(BER),error vector magnitude(EVM)and modulation error ratio(MER).Experimental results of the pilot study unambiguously confirmed the effectiveness of the proposed solution(longer effective communication range,higher immunity to interference,deployment of higher state QAM modulation formats,higher transmission speeds etc.),as the adaptive equalization significantly improved BER,MER and EVM parameters.The best results were achieved using the QR-RLS algorithm.The results measured on deployed QR-RLS algorithm had significantly better Eb/N0(improved by approx.20 dB)and BER values(difference by up to two orders of magnitude).

Firing activities in a fractional-order Hindmarsh–Rose neuron with multistable memristor as autapse

Considering the fact that memristors have the characteristics similar to biological synapses, a fractional-order multistable memristor is proposed in this paper. It is verified that the fractional-order memristor has multiple local active regions and multiple stable hysteresis loops, and the influence of fractional-order on its nonvolatility is also revealed. Then by considering the fractional-order memristor as an autapse of Hindmarsh–Rose(HR) neuron model, a fractional-order memristive neuron model is developed. The effects of the initial value, external excitation current, coupling strength and fractional-order on the firing behavior are discussed by time series, phase diagram, Lyapunov exponent and inter spike interval(ISI) bifurcation diagram. Three coexisting firing patterns, including irregular asymptotically periodic(A-periodic)bursting, A-periodic bursting and chaotic bursting, dependent on the memristor initial values, are observed. It is also revealed that the fractional-order can not only induce the transition of firing patterns, but also change the firing frequency of the neuron. Finally, a neuron circuit with variable fractional-order is designed to verify the numerical simulations.

Stability and multistability of synchronization in networks of coupled phase oscillators

Coupled phase oscillators usually achieve synchronization as the coupling strength among oscillators is increased beyond a critical value. The stability of synchronous state remains an open issue. In this paper, we study the stability of the synchronous state in coupled phase oscillators. It is found that numerical integration of differential equations of coupled phase oscillators with a finite time step may induce desynchronization at strong couplings. The mechanism behind this instability is that numerical accumulated errors in simulations may trigger the loss of stability of the synchronous state.Desynchronization critical couplings are found to increase and diverge as a power law with decreasing the integral time step. Theoretical analysis supports the local stability of the synchronized state. Globally the emergence of synchronous state depends on the initial conditions. Other metastable ordered states such as twisted states can coexist with the synchronous mode. These twisted states keep locally stable on a sparse network but lose their stability when the network becomes dense.

Weak signal detection method based on novel composite multistable stochastic resonance

The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer mechanism.We propose a novel composite multistable stochastic-resonance(NCMSR)model combining the Gaussian potential model and an improved bistable model.Compared with the traditional multistable stochastic resonance method,all the parameters in the novel model have no symmetry,the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system parameters.The model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation,the NCMSR model has a higher utilization of noise.Taking the output signal-to-noise ratio as the index,weak periodic signal is detected based on the NCMSR model in Gaussian noise andαnoise environment respectively,and the detection effect is good.The application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer race.The outstanding advantages of this method in weak signal detection are verified,which provides a theoretical basis for industrial practical applications.

The design, manufacture and application of multistable mechanical metamaterials-a state-of-the-art review

Multistable mechanical metamaterials are a type of mechanical metamaterials with special features,such as reusability,energy storage and absorption capabilities,rapid deformation,and amplified output forces.These metamaterials are usually realized by series and/or parallel of bistable units.They can exhibit multiple stable configurations under external loads and can be switched reversely among each other,thereby realizing the reusability of mechanical metamaterials and offering broad engineering applications.This paper reviews the latest research progress in the design strategy,manufacture and application of multistable mechanical metamaterials.We divide bistable structures into three categories based on their basic element types and provide the criterion of their bistability.Various manufacturing techniques to fabricate these multistable mechanical metamaterials are introduced,including mold casting,cutting,folding and three-dimensional/4D printing.Furthermore,the prospects of multistable mechanical metamaterials for applications in soft driving,mechanical computing,energy absorption and wave controlling are discussed.Finally,this paper highlights possible challenges and opportunities for future investigations.The review aims to provide insights into the research and development of multistable mechanical metamaterials.

Post-trans-arterial chemoembolization hepatic necrosis and biliary stenosis: Clinical charateristics and endoscopic approach

Liver cancer is the fifth most common tumor and the second highest death-related cancer in the world.Hepatocarcinoma(HCC)represents 90%of liver cancers.According to the Barcelona Clinic Liver Cancer group,different treatment options could be offered to patients in consideration of tumor burden,liver function,pa-tient performance status and biochemical marker serum concentration such as alpha-fetoprotein.Trans-arterial chemoembolization(TACE)is the treatment of choice in patients with diagnosis of unresectable HCC not eligible for liver trans-plantation,and preserved arterial supply.TACE is known to be safe and its com-plications are generally mild such as post-TACE syndrome,a self-resolving adverse event that occurs in about 90%of patients after the procedure.However,albeit rarely,more severe adverse events such as biloma,sepsis,hepatic failure,chemoagents induced toxicities,and post-TACE liver necrosis can occur.A prompt diagnosis of these clinical conditions is fundamental to prevent further complications.As a result,biliary stenosis could be a rare post-TACE necrosis complication and can be difficult to manage.Complications from untreated biliary strictures include recurring infections,jaundice,chronic cholestasis,and secon-dary biliary cirrhosis.