A spatial channel propagation model is presented. Consider a uniform linear antenna (ULA) at the base station (BS) and narrowband signals transmitted at the mobile. In two types of propagating environments: indoor and outdoor, performance of low spatial correlation is investigated and some results are provided, which are significant to analyze the performance of diversity systems and configuration of array. The results also show that the configuration of array with either smaller angular spread or bigger angle of arrival (AOA) dominates the impact on spatial correlation, and that increasing angular spread or decreasing AOA diminishes, or even eliminates this impact.

A reconfigurable cipher chip for accelerating DES is described, 3DES and AES computations that demand high performance and flexibility to accommodate large numbers of secure connections with heterogeneous clients. To obtain high throughput, we analyze the feasibility of high-speed reconfigurable design and find the key parameters affecting throughput. Then, the corresponding design, which includes the reconfiguration analysis of algorithms, the design of reconfigurable processing units and a new reconfigurable architecture based on pipeline and parallel structure, are proposed. The implementation results show that the operating frequency is 110 MHz and the throughput rate is 7 Gbps for DES, 2.3 Gbps for 3 DES and 1.4 Gbps for AES. Compared with the similar existing implementations, our design can achieve a higher performance.

As traditional two-parameter constant false alarm rate (CFAR) target detection algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images increases, small targets present more pixels in SAR images. So the target distribution is of much significance. Distribution-based CFAR detection algorithm is presented. We unite the pixels around the test cell, and estimate the distribution of test cell by them. Generalized Likelihood Ratio Test (GLRT) is used to deduce the detectors. The performance of the distribution-based CFAR (DBCFAR) detectors is analyzed theoretically. False alarms of DBCFAR detection are fewer than those of CFAR at the same detection rate. Finally experiments are done and the results show the performance of DBCFAR is out of conventional CFAR. False alarms of DBCFAR detection are concentrated while those of CFAR detection are dispersive.

Based on a Pade approximation, a wide-angle parabolic equation method is introduced for computing the multi- object radar cross section (RCS) for the first time. The method is a paraxial version of the scalar wave equation, which solves the field by marching them along the paraxial direction. Numerical results show that a single wide-angle parabolic equation run can compute multi-obj ect RCS efficiently for angles up to 45 ° . The method provides a new and efficient numerical method for computation electromagnetics.

Different from the other conventional radars, the over the horizon radar (OTHR) faces complicated nonlinear coordinate transform due to electromagnetic wave propagation and reflection in ionospheres. A significant problem is the phenomenon of multi-path propagation. Considering it, the coordinate registration algorithms of planar measurement model and spherical measurement model are respectively derived in detail. Noticeably, a new transforming expression of apparent azimuth and an integrated form of transforming expressions from measurement vector to ground state vector in coordinate registration algorithm of spherical measurement model are proposed. And then simulations are made to verify the correctness of the proposed algorithms and expression. Besides this, the transforming error rate of slant range, Doppler and apparent azimuth of the two kinds of models are given respectively. Then the quantitative analysis of error rate is also given. It can be drawn a conclusion that the coordinate registration algorithms of planar measurement model and spherical measurement model are both correct.

Moving object detection is one of the challenging problems in video monitoring systems, especially when the illumination changes and shadow exists. A method for real-time moving object detection is described. Anew background model is proposed to handle the illumination varition problem. With optical flow technology and background subtraction, a moving object is extracted quickly and accurately. An effective shadow elimination algorithm based on color features is used to refine the moving objects. Experimental results demonstrate that the proposed method can update the background exactly and quickly along with the varition ofillumination, and the shadow can be eliminated effectively. The proposed algorithm is a real-time one which the foundation for further object recognition and understanding of video monitoring systems.

The polarization filter using three orthogonal linear polarization antennas can suppress more disturbances than the polarization filter using two orthogonal linear polarization antennas in HF ground wave radar. But the algorithm of the threedimension filter is relatively complicated and not suitable for real-time processing. It can't use linear and nonlinear polarization vector translation technique directly. A modified polarization filter which is simple and has same suppressing ability as the three-dimension polarization filter is given. It only has half parameters of the primary one. Some problems about estimation of polarization parameters and selection of disturbances are discussed. A method of holding the phase of radar backscatter signal constantly is put forward so that unstationary disturbance signal can be processed.

A low complexity Per-Antenna Power Control (PAPC) approach based on Minimum Mean Squared Error (MMSE) detection for V-BLAST is proposed in this paper. The PAPC approach is developed for minimizing the Bit Error Rate (BER) averaged over all substreams when the data throughput and the total transmit power keep constant over time. Simulation results show that the Power-controlled V-BLAST (P-BLAST) outperforms the conventional V-BLAST in terms of BER performance with MMSE detector, especially in presence of high spatial correlation between antennas. However, the additional complexity for P-BLAST is not high. When MMSE detector is adopted, the P-BLAST can achieve a comparable BER performance to that of conventional V-BLAST with Maximum Likelihood (ML) detector but with low complexity.

Propose a new degradation call admission control(DCAC)scheme, which can be used in wideband code division multiple access communication system. So-called degradation is that non-real time call has the characteristic ofvariable bit rate, so decreasing its bit rate can reduce the load ofthe system, consequently the system can admit new call which should be blocked when the system is close to full load, therefore new call's access probability increases. This paper brings forward design project anddoessystemsimulation,simulation provesthatDCACcaneffectivelydecreasecalls'blockingprobabilityandincreasethe total number of the on-line users.

A fast knowledge based recognition method of the harbor target in large gray remote-sensing image is presented. First, the distributed features and the inherent feature are analyzed according to the knowledge of harbor targets; then, twomethods for extracting the candidate region of harbor are devised in accordance with different sizes of the harbors; after that, thresholds are used to segment the land and the sea with strategies of the segmentation error control; finally, harbor recognition is implemented according to its inherent character (semi-closed region of seawater).

To study the diagnostic problem of Wire-OR (W-O) interconnect fault of PCB (Printed Circuit Board), five modified boundary scan adaptive algorithms for interconnect test are put forward. These algorithms apply Global-diagnosis sequence algorithm to replace the equal weight algorithm of primary test, and the test time is shortened without changing the fault diagnostic capability. The descriptions of five modified adaptive test algorithms are presented, and the capability comparison between the modified algorithm and the original algorithm is made to prove the validity of these algorithms.

The concept of organization decision support system (ODSS) is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components: infrastructure, decision-making process and decision execution process. Infrastructure is responsible to transfer data and information. Decision-making process is the ODSS's soul to support decision-making. Decision execution process is to evaluate and execute decision results derived from decision-making process. The framework presents a kind of logic architecture. An example is given to verify and analyze the framework. The analysis shows that the framework has practical values, and has also reference values for understanding ODSS and for theoretical studies.

When analyze the uncertainty of the cost and the schedule of the spaceflight project, it is needed to know the value of the schedule-cost correlation coefficient. This paper deduces the schedule distribution, considering the effect of the cost, and proposes the estimation formula of the correlation coefficient between the ln(schedule) and the cost. On the basis of the fact and Taylor expansion, the relation expression between the schedule-cost correlation coefficient and the ln-schedule-cost correlation coefficient is put forward. By analyzing the value features of the estimation formula of the ln-schedule-cost correlation coefficient, the general rules are proposed to ascertain the value of the schedule-cost correlation coefficient. An example is given to demonstrate how to approximately amend the schedule-cost correlation coefficient based on the historical statistics, which reveals the traditional assigned value is inaccurate. The universality of this estimation method is analyzed.

In commanding decision-making, the commander usually needs to know a lot of situations(intelligence) on the adversary. Because of the military intelligence with opposability, it is inevitable that intelligence personnel take some deceptive information released by the rival as intelligence data in the process of intelligence gathering. Since the failure of intelligence is likely to lead to a serious aftereffect, the recognition of intelligence is a very important problem. An elementary research on recognizing military intelligence and puts forward a systematic processing method are made. First, the types and characteristics of military intelligence are briefly discussed, a research thought of recognizing military intelligence by means of recognizing military hypotheses are presented. Next, the reasoning mode and framework for recognizing military hypotheses are presented from the angle of psychology of intelligence analysis and non-monotonic reasoning. Then, a model for recognizing military hypothesis is built on the basis of fuzzy judgement information given by intelligence analysts. A calculative example shows that the model has the characteristics of simple calculation and good maneuverability. Last, the methods that selecting the most likely hypothesis from the survival hypotheses via final recognition are discussed.

The sources of supply chain enterprise risk from different aspects including material flow, information flow, cash flow and partner relationship is analyzed. Measures for risk reduction have also been summarized from the aspects of risk sharing, information sharing, change of inventory control mode, and supply chain flexibility. Finally, problems in current research on supply chain risk management are pointed out and a discussion on future research trend is presented.

The drawbacks of common nonlinear Filtered- ε adaptive inverse control (AIC) method, such as the unreliability due to the change of delay time and the faultiness existing in its disturbance control loop, are discussed. Based on it, the diagram of AIC is amended to accommodate with the characteristic of nonlinear object with time delay. The corresponding Filtered- ε adaptive algorithm based on RTRL is presented to identify the parameters and design the controller. The simulation results on a nonlinear ship model of "The R.O.V Zeefakkel" show that compared with the previous scheme and adaptive PID control, the improved method not only keeps the same dynamic response performance, but also owns higher robustness and disturbance rejection ability, and it is suitable for the control of nonlinear objects which have higher requirement to the maneuverability under complex disturbance environment.

Using the future desired input value, zero phase error controller enables the overall system's frequency response exhibit zero phase shift for all frequencies and a small gain error at low frequency range, and based on this, a new algorithm is presented to design the feedforward controller. However, zero phase error controller is only suitable for certain linear system. To reduce the tracking error and improve robustness, the design of the proposed feedforward controller uses a neural compensation based on diagonal recurrent neural network. Simulation and real-time control results for flight simulator servo system show the effectiveness of the proposed approach.

Using S-rough sets, this paper gives the concepts of f-heredity knowledge and its heredity coefficient, and f-variation coefficient of knowledge; presents the theorem of f-attribute dependence of variation coefficient and the relation theorem of heredity-variation. The attribute dependence of f-variation coefficient and the relation of heredity-variation are important characteristics of S-rough sets. From such discussion, this paper puts forward the heredity mining of  f-knowledge and the algorithm of heredity mining, also gives its relative application.

The robust stability test of time-delay systems with interval parameters can be concluded into the robust stability of the interval quasipolynomials. It has been revealed that the robust stability of the quasipolynomials depends on that of their edge polynomials. This paper transforms the interval quasipolynomials into two-dimensional (2-D) interval polynomials (2-D s-z hybrid polynomials), proves that the robust stability of interval 2-D polynomials are sufficient for the stability of given quasipolynomials. Thus, the stability test of interval quasipolynomials can be completed in 2-D s-z domain instead of classical 1-D s domain. The 2-D s-z hybrid polynomials should have different forms under the time delay properties of given quasipolynomials. The stability test proposed by the paper constructs an edge test set from Kharitonov vertex polynomials to reduce the number of testing edge polynomials. The 2-D algebraic tests are provided for the stability test of vertex 2-D polynomials and edge 2-D polynomials family. To verify the results of the pajser to be correct and valid, the simulations based on proposed results and comparison with other presented results are given.

A simple parametric approach to design a full-order observer for matrix second-order linear systems with uncertain disturbance input in the matrixsecond-order framework is proposed. The basic idea is to minimize the H2 norm of the transfer function from disturbance to estimation error using the design degrees of freedom provided by a parametric approach in the observer design. Besides the design parameters, the eigenvalues of the closed-loop system are also optimized within desired regions on the left-half of the complex plane. Using the proposed approach, additional specifications can be easily achieved. A spring-mass system is using to show the effect of the proposed approaches.

A newly designed approach of simultaneous stabilization is given for linear discrete time-delay systems. The problem of stabilization for a collection of systems is discussed initially. Adequate condition are obtained in terms of linear matrix inequalities (LMIs) which are independent of time delays such that the resultant collection of discrete time-delay systems are stable with an upper bound of the quadratic performance index. Subsequently, controllers are designed such that the resultant closed-loop discrete time-delay systems are simultaneously stabilized with the upper bound of the quadratic performance index. Finally,a numerical example is given to illustrate the design method.

Optimal deterministic disturbances rejection control problem for singularly perturbed linear systems is considered. By using the slow-fast decomposition theory of singular perturbation, the existent and unique conditions of the feedforward and feedback composite control (FFCC) laws for both infinite-time and finite-time are proposed, and the design approaches are given. A disturbance observer is introduced to make the FFCC laws realizable physically. Simulation results indicate that the FFCC laws are robust with respect to external disturbances.

A new output feedback adaptive control scheme for multi-input and multi-output nonlinear systems with parametric uncertainty is presented based on the Nussbaum gain method and the backstepping approach. The high frequency gain matrix of the linear part of the system is not necessarily positive definite, but can be transformed into a lower or upper triangular matrix whose signs of diagonal elements are unknown. The new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. The global stability of the closed loop systems is guaranteed through this control scheme, at the same time the tracking error converges to zero.

Decentralized robust stabilization problem of discrete-time fuzzy large-scale systems with parametric uncertainties is considered. This uncertain fuzzy large-scale system consists of N interconnected T-S fuzzy subsystems, and the parametric uncertainties are unknown but norm-bounded. Based on Lyapunov stability theory and decentralized control theory of large-scale system, the design schema of decentralized parallel distributed compensation (DPDC) fuzzy controllers to ensure the asymptotic stability of the whole fuzzy large-scale system is proposed. The existence conditions for these controllers take the forms of LMIs. Finally a numerical simulation example is given to show the utility of the method proposed.

Two design approaches of state feedback and output feedback tracking controllers are proposed for a class of strict feedback nonlinear time-delay systems by using backstepping technique. When the states of system cannot be observed, the time-delay state observer is designed to estimate the system states. Domination method is used to deal with nonlinear time-delay function under the assumption that the nonlinear time-delay functions of systems satisfy Lipschitz condition. The global asymptotical tracking of the reference signal is achieved and the bound of all signals of the resultant closed-loop system is also guaranteed. By constructing a Lyapunov-Krasoviskii functional, the stability of the closed-loop system is proved. The feasibility of the proposed approach is illustrated by a simulation example.

The distribution of sampling data influences completeness of rule base so that extrapolating missing rules is very difficult. Based on data mining, a self-learning method is developed for identifying fuzzy model and extrapolating missing rules, by means ofconfidence measure and the improved gradient descent method. The proposed approach can not only identify fuzzy model, update its parameters and determine optimal output fuzzy sets simultaneously, but also resolve the uncontrollable problem led by the regions that data do not cover. The simulation results show the effectiveness and accuracy of the proposed approach with the classical truck backer-upper control problem verifying.

A key problem of electronic commerce (for short e-commerce) is fair exchange which guarantees that at the end of the transaction, either both parties involved in the transaction receive each other's items or none do. A non-interactive optimistic fair exchange e-commerce protocol model based on the publicly verifiable secret sharing is presented. The main idea of our exchange protocol is to interchange verifiable and recoverable keys of the symmetric encryption for participants' items. So it is especially suitable for exchange of large-size items. Furthermore, our protocol is efficient and simple as it does not need interactive proof system which has been adopted by a large quantity of previously proposed fan- exchange protocols. Based on a modified (2,2) secret sharing scheme, a concrete non-interactive fair exchange e-commerce protocol is designed.

Genetic Algorithms (GA) are a search techniques based on mechanics of nature selection and have already been successfully applied in many diverse areas. However, increasing samples show that GA's performance is not as good as it was expected to be. Criticism of this algorithm includes the slow speed and premature result during convergence procedure. In order to improve the performance, the population size and individuals' space is emphatically described. The influence of individuals' space and population size on the operators is analyzed. And a novel family genetic algorithm (FGA) is put forward based on this analysis. In this novel algorithm, the optimum solution families closed to quality individuals is constructed, which is exchanged found by a search in the world space. Search will be done in this microspace. The family that can search better genes in a limited period of time would win a new life. At the same time, the best gene of this micro space with the basic population in the world space is exchanged. Finally, the FGA is applied to the function optimization and image matching through several experiments. The results show that the FGA possessed high performance.

Mixture model based image segmentation method, which assumes that image pixels are independent and do not consider the position relationship between pixels, is not robust to noise and usually leads to misclassification. A new segmentation method, called multi-resolution Gaussian mixture model method, is proposed. First, an image pyramid is constructed and son-father link relationship is built between each level of pyramid. Then the mixture model segmentation method is applied to the top level. The segmentation result on the top level is passed top-down to the bottom level according to the son-father link relationship between levels. The proposed method considers not only local but also global information of image, it overcomes the effect of noise and can obtain better segmentation result. Experimental result demonstrates its effectiveness.

Some structures of digital quadrature AD conversion for software-defined radio (SDR) systems are studied. Their performances and affections on the SDR systems are also analyzed. Two generalized quadrature AD schemes are proposed. In one of them, the AD sampling speed can be reduced by 2 times; and in the other both the output data rate of every channel and AD sampling speed can be lowered by paralleling the digital quadrature filtering structure. These structures can be also easily implemented into modules, and the polyphase filters can be flexibly realized by VHDL language based one chip of FPGA. To assess the proposed schemes, their applications to a particular ultra wideband (UWB) demonstrative receiver system are introduced. Some experimental results are also given. It is shown that the generalized quadrature AD structures are reliable and feasible for its module design, and performances are improved obviously for its better performance to price ratio.

The flexibility of traditional image processing system is limited because those system are designed for specific applications. In this paper, a new TMS320C64x-based multi-DSP parallel computing architecture is presented. It has many promising characteristics such as powerful computing capability, broad I/O bandwidth, topology flexibility, and expansibility. The parallel system performance is evaluated by practical experiment.

An enhaned NTRU cryptosystem eliminating decryption failures is proposed without using padding schemes and can resist the oracle model andchosen-ciphertext attacks. Because lattice reduction is the main threat to lattice-based cryptosystems, lattice reductionalgorithms are analyzed to evaluate the security of this scheme. Furthermore, the new scheme remains the advantage of high efficiency of original NTRU.

A new equalization method is proposed in this paper for severely nonlinear distorted channels. The structure of decision feedback is adopted for the non-singleton fuzzy regular neural network that is trained by gradient-descent algorithm. The model shows a much better performance on anti-jamming and nonlinear classification, and simulation is carried out to compare this method with other nonlinear channel equalization methods. The results show the method has the least bit error rate (BER).

To makesystem-of-systems combat simulation models easy to be developed and reused, simulation model formal specification and representation are researched. According to the view of system-of-systems combat simulation, and based on DEVS, the simulation model's fundamental formalisms are explored. It includes entity model, system-of-systems model and experiment model. It also presents rigorous formal specification. XML data exchange standard is combined to design the XML based language, SCSL, to support simulation model representation. The corresponding relationship between SCSL and simulation model formalism is discussed and the syntax and semantics of elements in SCSL are detailed. Based on simulation model formal specification, the abstract simulation algorithm is given and SCSL virtual machine, which is capable of automatically interpreting and executing simulation model represented by SCSL, is designed. Finally an application case is presented, which can show the validation of the theory and verification of SCSL.

Support vector machines (SVMs) are initially designed for binary classification. How to effectively extend them for multiclass classification is still an ongoing research topic. A multiclass classifier is constructed by combining SVM//g/" algorithm with directed acyclic graph SVM (DAGSVM) method, named DAGSVM/zgA/. A new method is proposed to select theworkingsetwhichisidenticaltotheworkingsetselectedbySVMhght approach.Experimentalresultsindicate DAGSVMlightis competitive with DAGSMO. It is more suitable for practice use. It may be an especially useful tool for large-scale multiclass classification problems and lead to more widespread use of SVMs in the engineering community due to its good performance.

To assure the shareholders can look for their "legal" attorneys to renew the secret, once the secret sharing scheme is initialized, a secret sharing scheme with inherited characteristic is constructed. In this scheme, each shareholder can produce a new share by his algorithm, which is equivalent to the primary one. Together with other shares, the primary secret can be renewed. Since this scheme is constructed not by replacing the primary share with a new share produced by the dealer in his primitive secret sharing scheme, so no matter how much shares the shareholder produces, these shares can not be gathered together to renew the secret in this scheme. Compared with the existing secret sharing schemes, this scheme provides more agility for the shareholders by investing each of them a function but not affect its security.

Function S-rough sets (function singular rough sets) is defined on a -function equivalence class [?]. Function S-rough sets is the extension form of S-rough sets. By using the function S-rough sets, this paper gives rough law generation model of a-function equivalence class, discussion on law mining and law discovery in systems, and application of law mining and law discovery in communication system. Function S-rough sets is a new theory and method in law mining research.

Routes in an ad hoc network may fail frequently because of node mobility. Stability therefore can be an important element in the design of routing protocols. The node escape probability is introduced to estimate the lifetime and stability of link between neighboring nodes and the escape probability based routing (EPBR) scheme to discover stable routes is proposed. Simulation results show that the EPBR can discover stable routes to reduce the number of route rediscovery, and is applicable for the situation that has highly dynamic network topology with broad area of communication.

It is a challenging problem to provide quality-of-service (QoS) guarantees in next generation high-speed network, and the QoS routing is one of the key issues of the problem. For the problem of multi-constrained QoS routing in high-speed network, especially under the inaccurate link state information, the success ratio of the different constraint combination is analyzed statistically, and a constraint analysis method based on the computer simulation is proposed. Furthermore, the approximately equal loose-tight order relation between each two constraints is constructed, and then an algorithm based on the experimental analysis is presented. Finally, the simulation result demonstrates that the algorithm has the higher success ratio, and the theoretical analysis proves its correctness and universality.