Adaptive unscented Kalman filter for parameter and state estimation of nonlinear high-speed objects

An adaptive unscented Kalman filter (AUKF) and an augmented state method are employed to estimate the timevarying parameters and states of a kind of nonlinear high-speed objects. A strong tracking filter is employed to improve the tracking ability and robustness of unscented Kalman filter (UKF) when the process noise is inaccuracy, and wavelet transform is used to improve the estimate accuracy by the variance of measurement noise. An augmented square-root framework is utilized to improve the numerical stability and accuracy of UKF. Monte Carlo simulations and applications in the rapid trajectory estimation of hypersonic artillery shells confirm the effectiveness of the proposed method.     

Generalized reliability measures of Kalman filtering for precise point positioning

To deal with the adverse influence of model failures on Kalman filtering (KF) estimation, it is necessary to investigate the generalized reliability theory, including the model failure detection and identification method as well as the separability and reliability theories. Although the generalized reliability theory for the least square has been discussed for many decades, the generalized reliability theory of KF is not widely discussed. Compared with the least square, KF includes not only the measurement model, but also the dynamic model. In KF, the predicted value of the state parameters from the dynamic model is considered as pseudomeasurements and combined with the observed measurements to compose the form of the least square. According to the reliability of the least square, the generalized reliability of KF is derived. Then, the dynamic model failure of precise point positioning is simulated to demonstrate the usage of the generalized reliability theory. The results show that the adverse influence of the dynamic model failure is more severe than that of the measurement model. Moreover, it is recommended that the model failure identification should always be used even if the overall model test passes. It is shown that the derived generalized reliability measures are suitable for the generalized KF estimation.     

Robust D-stability LMI conditions of matrix polytopes via affine parameter-dependent Lyapunov functions

The problem of the robust D-stability analysis for linear systems with parametric uncertainties is addressed. For matrix polytopes, new conditions via the affine parameter-dependent Lyapunov function of uncertain systems are developed with the benefit of the scalar multi-convex function. To be convenient for applications, such conditions are simplified into new linear matrix inequality （LMI） conditions, which can be solved by the powerful LMI toolbox. Numerical examples are provided to indicate that this new approach is less conservative than previous results for Hurwitz stability, Schur stability and D-stability of uncertain systems under certain circumstances.     

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.     

Collaborative multi-agent reinforcement learning based on experience propagation

For multi-agent reinforcement learning in Markov games, knowledge extraction and sharing are key research problems. State list extracting means to calculate the optimal shared state path from state trajectories with cycles. A state list extracting algorithm checks cyclic state lists of a current state in the state trajectory, condensing the optimal action set of the current state. By reinforcing the optimal action selected, the action policy of cyclic states is optimized gradually. The state list extracting is repeatedly learned and used as the experience knowledge which is shared by teams. Agents speed up the rate of convergence by experience sharing. Competition games of preys and predators are used for the experiments. The results of experiments prove that the proposed algorithms overcome the lack of experience in the initial stage, speed up learning and improve the performance.     

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.     

Trajectory shaping guidance law based on virtual angle with terminal constraints

A trajectory shaping guidance law based on virtua angle （TSGLBVA） is proposed for a re-entry vehicle with the constraints of terminal impact angles and their time derivatives. In the view of differential properties of the maneuvering trajectory, a virtual angle and a virtual radius are defined. Also, the shaping trajectory of the vehicle is established by the polynomials of the virtual angle. Then, four optimized parameters are selected according to the theorem of parameters transformation presented in this paper. Finally, a convergent variant of the Nelder-Mead algorithm is adopted to obtain the reference trajectory, and a trajectory feedback tracking guidance law is designed. The simulation results demonstrate that the TSGLBVA ensures the re-entry vehicle to impact a target precisely from a specified direction with smal terminal load factor command, as well as to obtain a maximum or constrained terminal velocity according to various requirements.     

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.     

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.     

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.     

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.     

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.     

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.     

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.