Measuring Nonlinear Dependence Between Time Series Based on Correlation Dimension

In this paper, it is proved that the correlation dimension estimate of a nonlinear dynamical system with its multivariate observation series is the same as that with its univariate observation series. Based on this result, an inference method is presented, and the Nonlinear Dependence Coefficient is defined. This method is designed for testing nonlinear dependence between time series, and can be used in economic analysis and forecasting. Numerical results show the method is effective.     

Survey on nonlinear reconfigurable flight control

An overview on nonlinear reconfigurable flight control approaches that have been demonstrated in flight-test or highfidelity simulation is presented. Various approaches for reconfigurable flight control systems are considered, including nonlinear dynamic inversion, parameter identification and neural network technologies, backstepping and model predictive control approaches. The recent research work, flight tests, and potential strength and weakness of each approach are discussed objectively in order to give readers and researchers some reference. Finally, possible future directions and open problems in this area are addressed.     

Edge-Fault-Tolerant Properties of Augmented Cubes

As an enhancement on the hypercube Qn, the augmented cube AQn, pro- posed by Choudum and Sunitha [Choudum S.A., Sunitha V., Augmented cubes, Networks, 40（2）（2002）, 71-84], possesses some properties superior to the hypercube Qn. In this paper, assuming that （u, v） is an arbitrary fault-free d-link in an n-dimensional augmented cubes, 1 ≤ d ≤ n - 1, n ≥ 4. We show that there exists a fault-free Hamiltonian cycle in the augmented cube contained （u, v）, even if there are 2n - 3 link faults.     

Exponential Stability of a Robot with Safety System

This paper presents the analysis of exponential stability of a system consisting of a robot and its associated safety mechanism. The system have various modes of failures and is repairable. The paper investigates the nonnegative stead-state solution of system,the existence of strictly dominant eigenvalue and restriction of essential spectrum growth bound of the system operator. The essential spectral radius of the system operator is also discussed before and after perturbation. The results show that the dynamic solution of the system is exponential stab＇flity and converges to the steady-state solution.     

Dual loop feedback pre-distortion in satellite communication

Since the satellite communication goes in the trend of high-frequency and fast speed, the coefficients updating and the precision of the traditional pre-distortion feedback methods need to be further improved. On this basis, this paper proposes dual loop feedback pre-distortion, which uses two first-order Volterra filter models to reduce the computing complexity and a dynamic error adjustment model to construct a revised feedback to ensure a better pre-distortion performance. The computation complexity, iterative convergence speed and precision of the proposed method are theoretically analyzed. Simulation results show that this dual loop feedback pre-distortion can speed the updating of coefficients and ensure the linearity of the amplifier output.     

Cryptanalysis of Hwang et al.＇s Improved Encryption Scheme

Recently, Tseng et al. proposed authenticated encryption scheme with message recovery using self-certified public keys. Hwang et al. proposed an attack to show that the Tseng et al.＇s scheme was not secure. And Hwang et al. proposed an improved scheme and claimed to that the new scheme satisfy the security requirement. However, we will show that the improved signature proposed by Hwang et al. is still insecure.     

On the Merrifield-Simmons Indices and Hosoya Indices of Cyclic Graphs

The Merrifield-Simmons index and Hosoya index are defined as the number of the graph G（V, E） as the number of subsets of V（G） in which no tow vertices are adjacent and the number of subsets of E（G） in which no two edges are incident, respectively. In this paper, we characterize the Unicyclic graphs with Merrifield-Simmons indices and Hosoya indices, respectively. And double-cyclic graphs with Hosoya indices among the doublecyclic graphs with n vertices.     

Control and Synchronization of a Novel Hyperchaotic System Containing One Quadratic Term

A novel hyperchaotic system derived from Liu system is proposed in this paper. Lyapunov exponent, phase portrait and Poincare mapping are given to verify that the system is hyperchaotic. A controller is designed to compel the hyperchaotic system to converge into the equilibrium. It is proved theoretically that this control law is feasible and valid by Lyapunov second method. Based on linear feedback synchronization control principle, synchronization control of the novel hyperchaotic system is realized. Numerical simulation shows that this synchronization method is simple and effective. As long as the proper linear feedback control vector is chosen, it is easy to achieve the rapid synchronization between the driving system and response system.     

The Influences of FDI on China＇s Economy

During the past 30 years, China has attracted huge amounts of Foreign Direct Investment （FDI） inflows and FDI firms have become an important element of the Chinese economy. The paper discusses the influence of FDI on China＇s economy, summarizes the analysis of the external effects of FDI and focuses on the domestic effects of FDI.     

Synergistic Performance Management System and Its Associated Structural Model

Aiming at the widespread issues of synergistic performance management, a conceptual model of synergistic performance management system is built. The order parameter of system synergy and the main factors, as well as the degree of synergy and the concept of synergistic effect are proposed. An associated structural model of synergistic performance management system is established based on the method of structural equation modeling.     

A Credit Risk Evaluation Approach to Neural Network Training by Means of Financial Ratios

In recent years artificial neural networks are used to recognize the risk category of investigated companies. The research is based on data from 81 listed enterprises that applied for credit in domestic regional banks operating in China. The backpropagation algorithm-the multilayer feedforward network structure is described. Each firm is described by 9 diagnostic variables and potential borrowers are classified into four classes. The efficiency of classification is evaluated in terms of classification errors calculated from the actual classification made by the credit officers. The results of the experiments show that LevenbergMarque training error is smallest among 4 learning algorithms and its performance is better, and application of artificial neural networks and classification functions can support the creditworthiness evaluation of borrowers.     

Multi-view ladar data registration in obscure environment

Multi-view laser radar (ladar) data registration in obscure environments is an important research field of obscured target detection from air to ground. There are few overlap regions of the observational data in different views because of the occluder, so the multi-view data registration is rather difficult. Through indepth analyses of the typical methods and problems, it is obtained that the sequence registration is more appropriate, but needs to improve the registration accuracy. On this basis, a multi-view data registration algorithm based on aggregating the adjacent frames, which are already registered, is proposed. It increases the overlap region between the pending registration frames by aggregation and further improves the registration accuracy. The experiment results show that the proposed algorithm can effectively register the multi-view ladar data in the obscure environment, and it also has a greater robustness and a higher registration accuracy compared with the sequence registration under the condition of equivalent operating efficiency.     

Application of Disaggregated Logit Modeling with Stated Preference Method in Park and Ride Behavior for Non-local Private Car Travelers in Big Events

During big events, non-local private car travelers can be divided into two types which were returning in one day and in several days. It was demonstrated that those two kinds of travelers have distinct behavior on park and ride （P＆R）, due to their different travel demand and behavior attributes. In this paper focusing on the travelers returning in several days, the travel attributes and requirements for P＆R were analyzed with stated preference survey. A P＆R choice behavior disaggregated logit model was established and calibrated based on random utility theory. The model concludes three variables, which were travel time, parking fee and comprehensive attractiveness index for suburban satellite towns comparing to urban district. The results revealed that for travelers returning in several days the primary key point is increasing the attractiveness of suburban satellite towns.     

Cued search algorithm with uncertain detection performance for phased array radars

A cued search algorithm with uncertain detection performance is proposed for phased array radars. Firstly, a target search model based on the information gain criterion is presented with known detection performance, and the statistical characteristic of the detection probability is calculated by using the fluctuant model of the target radar cross section （RCS）. Secondly, when the detection probability is completely unknown, its probability density function is modeled with a beta distribution, and its posterior probability distribution with the radar observation is derived based on the Bayesian theory. Finally simulation results show that the cued search algorithm with a known RCS fluctuant model can achieve the best performance, and the algorithm with the detection probability modeled as a beta distribution is better than that with a random selected detection probability because the model parameters can be updated by the radar observation to approach to the real value of the detection probability.     

Hybrid micromotion-scattering center model for synthetic aperture radar micromotion target imaging

Micromotion is an important target feature, although the target micromotion has an unfavorable influence on the synthetic aperture radar （SAR） image interpretation due to defocusing. This paper introduces micromotion parameters into the scattering center model to obtain a hybrid micromotion-scattering center model, and then proposes an optimization algorithm based on the maximal likelihood estimation to solve the model for jointly obtaining target motion and scattering parameters. Initial value estimation methods using targets＇ ghost images are then presented to guarantee the global and fast convergence. Simulation results show the effectiveness of the proposed algorithm especially in high precision estimation and multiple targets processing.     

Forgery Attacks on Wang＇s Signature Schemes Based on Factoring and Discrete Logarithm

To enhance the security of signature schemes, Wang proposed two signature schemes based on the difficulties of simultaneously solving the factoring and discrete logarithm＇ problems with almost the same sizes of arithmetic modulus. This paper, firstly, shows that Wang＇s signature scheme 1 do not satisfy the claimed properties. Moreover, we will point out that the all variants of Wang＇s scheme 2 are not secure if attackers can solve discrete logarithm problems.     

Initial Value Sensitivity in Technology Diffusion

Initial value sensitivity in technology diffusion, an important problem for firms＇ decision making such as the timing and target market chosen for new technology or product entering the market, has long been limited by the research methodology and tool. Based on the network extension of Bass model, this paper proposes a stochastic threshold model and uses computer simulation to empirically examine three propositions on initial value sensitivity in technology diffusion process. Our findings suggest that diffusion extent is sensitive to not only the number of initial adopters but also their positions in social network, and the variance of customers＇ initial assessment as well, which can be detailed as follows： （1） the degree of technology diffusion exhibits highly positive relation to initial adopter quantity, in particular, when the quantity of initial adopters is small, diffusion extent is very sensitive; （2） diffusion extent is sensitive to the positions of initial adopters; （3） in addition, the variance of customers＇ initial evaluation displays strong negative relation to the final diffusion degree in that the larger variance, the lower of diffusion extent.     

Coded aperture compressive imaging array applied for surveillance systems

This paper proposes an application of compressive imaging systems to the problem of wide-area video surveillance systems. A parallel coded aperture compressive imaging system and a corresponding motion target detection algorithm in video using compressive image data are developed. Coded masks with random Gaussian, Toeplitz and random binary are utilized to simulate the compressive image respectively. For compressive images, a mixture of the Gaussian distribution is applied to the compressed image field to model the background. A simple threshold test in compressive sampling image is used to declare motion objects. Foreground image retrieval from underdetermined measurement using the total variance optimization algorithm is explored. The signal-to-noise ratio （SNR） is employed to evaluate the image quality recovered from the compressive sampling signals, and receiver operation characteristic （ROC） curves are used to quantify the performance of the motion detection algorithm. Experimental results demonstrate that the low dimensional compressed imaging representation is sufficient to determine spatial motion targets. Compared with the random Gaussian and Toeplitz mask, motion detection algorithms using the random binary phase mask can yield better detection results. However using the random Gaussian and Toeplitz phase mask can achieve high resolution reconstructed images.     

Anti-synchronization of Chaotic Neural Networks with Time Delay

In the paper, the anti-synchronization problem of the general delayed chaotic neural networks is investigated. For the master and slave systems, we obtain a control law to achieve the state anti-synchronization of two identical chaotic neural networks. By using the Halanay inequality lemma and Lyapunov stability method, we derive a delay indepen- dent sufficient exponential anti-synchronization condition relative to the parameters of the systems and controller gain matrix. The condition is easily verified in practice. Finally, the theoretical results are applied to two delayed chaotic neural networks, and numerical simulations are given to demonstrate the performance of the proposed scheme throughout some examples.     

Application of Matter-element and Information Entropy in Distribution Analysis of Railway Stations Dealing with Refrigeration Containers

Distributing of the railway refrigeration container handling stations is influenced by multitudinous factors, such as technique and equipment conditions, intermodal traffic ability, foreground and social economy conditions of the district. In this paper a maiden adoption of the matter-element is applied to combine with information entropy theory to analyze distributing the railway refrigeration container handling stations based on concerned literature and historical data, and a multi-objective decision-making model on analyzing distributing the railway refrigeration container handling stations is set up based on matter-element and extension model. Based on establishing sutra field and controlled field, we apply relating function of matter- element and extension set to get relating function value of the railway refrigeration container handling stations. Finally a case study is carried out to verify the validity, objectivity and applicability of this model through calculated and compared with traditional analysis methods. Practicality application indicates that this method can avoid subjectivity of weighting, but enhance the extensibility, the model mentioned above has guiding significance and applied value for analyzing distributing the railway refrigeration container handling stations.