As one of the next generation imaging spectrometers, the interferential spectrometer (IS) possesses the advantages of high throughput, multi-channel and great resolution. The data of IS are produced in the spatial domain, but optical applications are in the Fourier domain. Traditional compression methods can only protect the visual quality of interferometer data in the spatial domain but ignore the distortion in the Fourier domain. The relation between the distortion in the Fourier domain and the compression in the spatial domain is analyzed. By mathematical proof and validation with experiments, the relation between spatial and Fourier domains is discovered, and the significance in the Fourier domain is more important as optical path difference (OPD) increasing in the spatial domain. Based on this relation, a novel coding scheme is proposed, which can compress data in the spatial domain while reducing the distortion in the Fourier domain. In this scheme, the bit stream of the set partitioning in hierarchical trees (SPIHT) is truncated by adaptively lifting rate-distortion slopes according to the priorities of OPD based on rate-distortion optimization theory. Experimental results show that the proposed method can provide better protection of spectrum curves in the Fourier domain while maintaining a comparable visual quality in the spatial domain.

A dual-channel access mechanism to overcome the drawback of traditional single-channel access mechanism for network-on-chip (NoC) is proposed. In traditional single-channel access mechanism, every Internet protocol (IP) has only one channel to access the on-chip network. When the network is relatively idle, the injection rate is too small to make good use of the network resource. When the network is relatively busy, the ejection rate is so small that the packets in the network cannot leave immediately, and thus the probability of congestion is increased. In the dual-channel access mechanism, the injection rate of IP and the ejection rate of the network are increased by using two optional channels in network interface (NI) and local port of routers. Therefore, the communication performance is improved. Experimental results show that compared with traditional single-channel access mechanism, the proposed scheme greatly increases the throughput and cuts down the average latency with reasonable area increase.

In some object tracking systems, the moving object future position is an area (i.e., target area). It is a successful estimation strategy if the predicted points fall in the target area. If the object makes a sudden maneuvering, the prediction may get out of the target area easily which may make the tracking system lose the object. The aim is to investigate the admissible maximum object maneuvering intensity, which is characterized as model noise variance, for such kind of tracking system. Firstly, the concept of stochastic passage characteristics over the boundary of target area and their relationship with prediction error variance are described. Secondly, the consistency among the indices of regional pole, prediction error variance and stochastic passage characteristics is analyzed. Thirdly, the multi-indices constraints are characterized by a set of bi-linear matrix inequalities (BMIs). Then, the admissible maximum model noise variance and the satisfactory estimation strategy are presented by iteratively solving linear matrix inequalities (LMIs) to approximate BMIs. Finally, a numerical example is proposed to demonstrate the obtained results.

H-infinity estimator is generally implemented in timevariant state-space models, but it leads to high complexity when the model is used for multiple input multiple output with orthogonal frequency division multiplexing (MIMO-OFDM) systems. Thus, an H-infinity estimator over time-invariant system models is proposed, which modifies the Krein space accordingly. In order to avoid the large matrix inversion and multiplication required in each OFDM symbol from different transmit antennas, expectation maximization
(EM) is developed to reduce the high computational load. Joint estimation over multiple OFDM symbols is used to resist the high pilot overhead generated by the increasing number of transmit antennas. Finally, the performance of the proposed estimator is enhanced via an angle-domain process. Through performance analysis and simulation experiments, it is indicated that the proposed algorithm has a better mean square error (MSE) and bit error rate (BER) performance than the optimal least square (LS)
estimator. Joint estimation over multiple OFDM symbols can not only reduce the pilot overhead but also promote the channel performance. What is more, an obvious improvement can be obtained by using the angle-domain filter.

A new filtering method for SAR data de-noising using wavelet support vector regression (WSVR) is developed. On the basis of the grey scale distribution character of SAR imagery, the logarithmic SAR image as a noise polluted signal is taken and the noise model assumption in logarithmic domain with Gaussian noise and impact noise is proposed. Based on the better performance of support vector regression (SVR) for complex signal approximation and the wavelet for signal detail expression, the wavelet kernel function is chosen as support vector kernel function. Then the logarithmic SAR image is regressed with WSVR. Furthermore the regression distance is used as a judgment index of the noise type. According to the judgment of noise type every pixel can be adaptively de-noised with different filters. Through an approximation experiment for a one-dimensional complex signal, the feasibility of SAR data regression based on WSVR is confirmed. Afterward the SAR image is treated as a two-dimensional continuous signal and filtered by an SVR with wavelet kernel function. The results show that the method proposed here reduces the radar speckle noise effectively while maintaining edge features and details well.

The mean shift tracker has difficulty in tracking fast moving targets and suffers from tracking error accumulation problem. To overcome the limitations of the mean shift method, a new approach is proposed by integrating the mean shift algorithm and frame-difference methods. The rough position of the moving target is first located by the direct frame-difference algorithm and three-frame-difference algorithm for the immobile camera scenes and mobile camera scenes, respectively. Then, the mean shift algorithm is used to achieve precise tracking of the target. Several tracking experiments show that the proposed method can effectively track first moving targets and overcome the tracking error accumulation problem.

A generalization of the linguistic aggregation functions (or operators) is presented by using generalized and quasiarithmetic means. Firstly, the linguistic weighted generalized mean (LWGM) and the linguistic generalized ordered weighted averaging (LGOWA) operator are introduced. These aggregation functions use linguistic information and generalized means in the weighted average (WA) and in the ordered weighted averaging (OWA) function. They are very useful for uncertain situations where the available information cannot be assessed with numerical values but it is possible to use linguistic assessments. These aggregation operators generalize a wide range of aggregation operators that use linguistic information such as the linguistic generalized mean (LGM), the linguistic OWA (LOWA) operator and the linguistic ordered weighted quadratic averaging (LOWQA) operator. We also introduce a further generalization by using quasi-arithmetic means instead of generalized means obtaining the quasi-LWA and the quasi-LOWA operator. Finally, we develop an application of the new approach where we analyze a decision making problem regarding the selection of strategies.

The cross-efficiency evaluation method is reviewed which is developed as a data envelopment analysis (DEA) extensive tool. The cross-efficiency evaluation method is utilized to identify the decision making unit (DMU) with the best practice and to rank the DMUs by their respective cross-efficiency scores. The main drawbacks of the cross-efficiency evaluation method when the ultimate average cross-efficiency scores are used to evaluate and rank the DMUs are also pointed out. With the research gap, an improved technique for order preference by similarity to ideal solution (TOPSIS) is introduced to rank the cross-efficiency by eliminating the average assumption. Finally, an empirical example is illustrated to examine the validity of the proposed method.

In rough communication, because each agent has a different language and can not provide precise communication to each other, the concept translated among multi-agents will loss some information, and this results in a less or rougher concept. With different translation sequences the amount of the missed knowledge is varied. The λ−optimal translation sequence of rough communication, which concerns both every agent and the last agent taking part in rough communication to get information as much as he (or she) can, is given. In order to get the λ−optimal translation sequence, a genetic algorithm is used. Analysis and simulation of the algorithm demonstrate the effectiveness of the approach.

The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors. The MGM(1,m) with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM(1,2) with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.

Task-oriented networked information system is an integrated information system which builds on multi-satellite networking to accomplish one or more tasks. In the background of emergency relief for applications, system working flow and response process are analyzed, and a timeliness effectiveness evaluation index system is constructed at multi-task level. The effectiveness is a measurement of promptness of information return. In evaluation process, system performance and tasks are associated, then an evaluation model based on efficacy function is established, and different evaluation criteria are selected for different tasks. A distributed simulation system is constructed, and the execution of task is decomposed. The simulation platform provides a comprehensive data source for evaluation. The results are easy to compare with each other, which reflects system time efficiency in different satellites networks and provides actual systems with basis and reference for design and application.

An ant colony optimization (ACO)-simulated annealing (SA)-based algorithm is developed for the target assignment problem (TAP) in the air defense (AD) command and control (C2) system of surface to air missile (SAM) tactical unit. The accomplishment process of target assignment (TA) task is analyzed. A firing advantage degree (FAD) concept of fire unit (FU) intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat.

According to the characteristic and the requirement of multipath planning, a new multipath planning method is proposed based on network. This method includes two steps: the construction of network and multipath searching. The construction of network proceeds in three phases: the skeleton extraction of the configuration space, the judgment of the cross points in the skeleton and how to link the cross points to form a network. Multipath searching makes use of the network and iterative penalty method (IPM) to plan multi-paths, and adjusts the planar paths to satisfy the requirement of maneuverability of unmanned aerial vehicle (UAV). In addition, a new height planning method is proposed to deal with the height planning of 3D route. The proposed algorithm can find multiple paths automatically according to distribution of terrain and threat areas with high efficiency. The height planning can make 3D route following the terrain. The simulation experiment illustrates the feasibility of the proposed method.

Perturbation and robust controllability of the singular distributed parameter control system are discussed via functional analysis and the theory of GE-semigroup in Hilbert space. The perturbation principle of GE-semigroup and the sufficient condition concerning the robust controllability of the singular distributed parameter control system are obtained, in which the controllability for singular distributed parameter control system is not destroyed, if we perturb the equation by small bounded linear operator.

The relationship between the technique by statedependent Riccati equations (SDRE) and Hamilton-Jacobi-Isaacs (HJI) equations for nonlinear H∞ control design is  investigated. By establishing the Lyapunov matrix equations for partial derivates of the solution of the SDREs and introducing symmetry measure for some related matrices, a method is proposed for examining whether the SDRE method admits a global optimal control equivalent to that solved by the HJI equation method. Two examples with simulation are given to illustrate the method is effective.

The guaranteed cost control for a class of uncertain discrete-time networked control systems with random delays is addressed. The sensor-to-controller (S-C) and contraller-to-actuator (C-A) random network-induced delays are modeled as two Markov chains. The focus is on the design of a two-mode-dependent guaranteed cost controller, which depends on both the current S-C delay and the most recently available C-A delay. The resulting closed-loop systems are special jump linear systems. Sufficient conditions for existence of guaranteed cost controller and an upper bound of cost function are established based on stochastic Lyapunov-Krasovakii functions and linear matrix inequality (LMI) approach. A simulation example illustrates the effectiveness of the proposed method.

Leader-following stationary consensus problem is investigated for the second-order multi-agent systems with timevarying communication delay and switching topology. Based on Lyapunov-Krasovskii functional and Lyapunov-Razumikhin functions respectively, consensus criterions in the form of linear matrix inequality (LMI) are obtained for the system with time-varying communication delays under static interconnection topology converging to the leader’s states. Moreover, the delay-dependent consensus
criterion in the form of LMI is also obtained for the system with time-invariant communication delay and switching topologies by constructing Lyapunov-Krasovskii functional. Numerical simulations present the correctness of the results.

The incoherent control of finite-level quantum systems is investigated. Following a brief introduction to coherent control paradigms in quantum control, a control problem that can not be accomplished using only coherent control is presented. For such a control problem, it is proved that it can be accomplished using incoherent control based on projective measurement and coherent control for two classes of finite-level quantum systems, i.e., eigenstate controllable quantum systems and wavefunction controllable
quantum systems.

A new non-decoupling three-dimensional guidance law is proposed for bank-to-turn (BTT) missiles with the motion coupling problem. In this method, the different geometry is taken for theoretically modeling on BTT missiles’ motion within the threedimensional style without information loss, and meanwhile, Liegroup is utilized to describe the line-of-sight (LOS) azimuth when the terminal angular constraints are considered. Under these circumstances, a guidance kinematics model is established based on differential geometry. Then, corresponding to no terminal angular constraint and terminal angular constraints, guidance laws are respectively designed by using proportional control and generalized proportional-derivative (PD) control in SO(3) group. Eventually, simulation results validate that this developed method can effectively avoid the complexity of pure Lie-group method and the information loss of the traditional decoupling method as well.

The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-filling theorem, a novel one-user water-filling algorithm is proposed, and then the corresponding simulation results are given to analyze the feasibility and validity. After that this algorithm is used to solve the communication utility optimization problem subject to the power constraints in cognitive radio network. First, through the gain to noise ratio for cognitive users, a subcarrier and power allocation algorithm based on the optimal frequency partition is proposed for two cognitive users. Then the spectrum sharing algorithm is extended to multiuser conditions such that the greedy and parallel algorithms are proposed for spectrum sharing. Theory and simulation analysis show that the subcarrier and power allocation algorithms can not only protect the primary users but also effectively solve the spectrum and power allocation problem for cognitive users.

A new incremental support vector machine (SVM) algorithm is proposed which is based on multiple kernel learning. Through introducing multiple kernel learning into the SVM incremental learning, large scale data set learning problem can be solved effectively. Furthermore, different punishments are adopted in allusion to the training subset and the acquired support vectors, which may help to improve the performance of SVM. Simulation results indicate that the proposed algorithm can not only solve the model selection problem in SVM incremental learning, but also improve the classification or prediction precision.

The estimation of generalized exponential distribution based on progressive censoring with binomial removals is presented, where the number of units removed at each failure time follows a binomial distribution. Maximum likelihood estimators of the parameters and their confidence intervals are derived. The expected time required to complete the life test under this censoring scheme is investigated. Finally, the numerical examples are given to illustrate some theoretical results by means of Monte-Carlo simulation.

A method of object detection based on combination of local and spatial information is proposed. Firstly, the categorygiven representative images are chosen through clustering to be templates, and the local and spatial information of template are extracted and generalized as the template feature. At the same time, the codebook dictionary of local contour is also built up. Secondly, based on the codebook dictionary, sliding-window mechanism and the vote algorithm are used to select initial candidate object windows. Lastly, the final object windows are got from initial candidate windows based on local and spatial structure feature matching. Experimental results demonstrate that the proposed approach is able to consistently identify and accurately detect the objects with better performance than the existing methods.