To recognize circular objects rapidly in satellite remote sensing imagery, an approach using their geometry properties is presented. The original image is segmented to be a binary one by one dimension maximum entropy threshold algorithm and the binary image is labeled with an algorithm based on recursion technique. Then, shape parameters of all labeled regions are calculated and those regions with shape parameters satisfying certain conditions are recognized as circular objects. The algorithm is described in detail, and comparison experiments with the randomized Hough transformation (RHT) are also provided. The experimental results on synthetic images and real images show that the proposed method has the merits of fast recognition rate, high recognition efficiency and the ability of anti-noise and anti-jamming. In addition, the method performs well when some circular objects are little deformed and partly misshapen.

The novel closed–form expressions for the average channel capacity of dual selection diversity is presented, as well as, the bit-error rate (BER) of several coherent and noncoherent digital modulation schemes in the correlated Weibull fading channels with nonidentical statistics. The results are expressed in terms of Meijer’s Gfunction, which can be easily evaluated numerically. The simulation results are presented to validate the proposed theoretical analysis and to examine the effects of the fading severity on the concerned quantities.

To study the scene classification in the Synthetic Aperture Radar (SAR) image, a novel method based on kernel estimate, with the Markov context and Dempster-Shafer evidence theory is proposed. Initially, a nonparametric Probability Density Function (PDF) estimate method is introduced, to describe the scene of SAR images. And then under the Markov context, both the determinate PDF and the kernel estimate method are adopted respectively, to form a primary classification. Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification. Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification. Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results. Experimental results on real SAR images illustrate a rather impressive performance.

A novel approach is proposed for speckle reduction in multilook full polarimetric SAR images. In contrast to others, this approach adopts an enhanced structure detection method to estimate the parameters of the polarimetric covariance matrix for the multilook polarimetric whitening filtering (MPWF) algorithm and thus a structural adaptive and optimal speckle filter is developed. To evaluate the present approach, NASA SIR-C/XSAR, L band, four-look processed polarimetric SAR data of the Tian-Mountain Forest is used for simulation. Experimental results demonstrate the effectiveness of this novel filtering algorithm in case of both speckle reduction and preservation of texture information. Comparisons with other methods are also made.

Many properties of frequency-hopped spread-spectrum multiple access (FH/SSMA), such as, robustness against frequency selective fading and jamming make it a preferred multiple access communication scheme. But cochannel interference (CCI) can seriously harm the system’s performance. On the basis of the analysis of the CCI pattern of frequency hopped multiple access signal, a new multiuser detection algorithm for canceling the CCI in frequency hopped multiple access systems is proposed. In the proposed scheme, the CCI is canceled by first detecting the frequency hopping slot, and then classifying and regenerating the candidates of the interference pattern from the time-frequency matrix. Both the theoretical analysis and computer simulation results show that compared to the conventional detector and Mabuchi’s detector, this new multiuser detector has lower complexity, better convergence stability, and is suitable for both additive white Gaussian noise (AWGN) channels and Rayleigh fading channels.

Maximal-ratio transmission systems with transmit antenna selection is investigated. According to the order statistics of channel flat fading coefficients, the closed-form expressions are derived for average SNR with any amount of RF chains and average BER with two RF chains, respectively. The algorithm for calculating the minimum of total transmit antennas is presented in terms of reduced RF chains. The method of quantizing transmit precoders is employed in this study to decrease feedback information. Simulation results demonstrate the superiority of the proposed systems under full and quantized transmit precoders. The SNR of the proposed systems has been less degraded by the quantization of transmit precoder than that of pure maximal-ratio transmission systems.

To suppress the interference in the ultra-wideband (AI-UWB) system is a challenging problem. An anti-interference multiband orthogonal frequency-division multiplexing ultra-wideband (AI-UWB) system, based on spreading and interleaving is addressed. It will exploit the frequency diversity across the subcarriers and provide the robustness to narrow-band interference, by spreading the coded bit streams within each sub-band and interleaving across all sub-bands. Simulating results show that the spreading and interleaving provide about 5 dB to 10 dB advantages over the conventional multiband orthogonal frequency-division multiplexing ultra-wideband system in signal-to-interference ratio. Spreading and interleaving is an effective cure for enhancing the robustness to narrowband interference.

To estimate the angle of arrivals (AOA) of wideband chirp sources, a new time-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution (RWVD) of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio (SNR) condition, the proposed method exhibits better precision than the method of frequency focusing (FF). The proposed method can be further applied to nonuniform linear array (NLA) since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.

Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals. The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio (SNR) variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron (MLP) classifier with better generalization, as well as, addition of time-frequency features set for classifying six different modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier.

UHF surface velocities radar is developed based on the successful ocean state measuring and analyzing radar system. The design method for UHF radar system is presented. It is designed to operate at UHF channel, and the transmit power is under 5W. Maximum range of field test over fresh water can be a kilometer. The field tests at Tangsun River and at Majiatan and Gaobazhou proved that USVR System can be used successfully.

Using function one direction S-rough sets (function one direction singular rough sets), f-law and Flaw and the concept of law distance and the concept of system law collided by F-law are given. Using these concepts, state characteristic presented by system law collided by F-law and recognition of these states characteristic and recognition criterion and applications are given. Function one direction S-rough sets is one of basic forms of function S-rough sets (function singular rough sets). Function one direction S-rough sets is importance theory and is a method in studying system law collision.

The uncertain multi-attribute decision-making problems because of the information about attribute weights being known partly, and the decision maker’s preference information on alternatives taking the form of interval numbers complementary to the judgment matrix, are investigated. First, the decision-making information, based on the subjective uncertain complementary preference matrix on alternatives is made uniform by using a translation function, and then an objective programming model is established. The attribute weights are obtained by solving the model, thus the overall values of the alternatives are gained by using the additive weighting method. Second, the alternatives are ranked, by using the continuous ordered weighted averaging (C-OWA) operator. A new approach to the uncertain multi-attribute decision-making problems, with uncertain preference information on alternatives is proposed. It is characterized by simple operations and can be easily implemented on a computer. Finally, a practical example is illustrated to show the feasibility and availability of the developed method.

Based on the actual experience of cooperation in the supply chain, the Nash solution of two enterprises cooperative games is given. Not only is the solution unique, but it is also stable, and neither side has the capability to deviate the allocation of interests from the equilibrium point. If some firm tries to withdraw from cooperation or threaten to use other particular strategy, the negotiations are likely to achieve the distribution by the threat game; The calculating method of the choice of the optimal bargaining base point and the corresponding optimal pay-off vector are given.

In order to rapidly and effectively meet the informative demand from commanding decision-making, it is important to build, maintain and mine the intelligence database. The type, structure and maintenance of military intelligence database are discussed. On this condition, a new data-mining arithmetic based on relation intelligence database is presented according to the preference information and the requirement of time limit given by the commander. Furthermore, a simple calculative example is presented to prove the arithmetic with better maneuverability. Lastly, the problem of how to process the intelligence data mined from the intelligence database is discussed.

Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.

Based on bounded network-induced time-delay, the networked control system is modeled as a linear time-variant singular system. Using the Lyapunov theory and the linear matrix inequality approach, the criteria for delay-independent stability and delay-dependent stability of singular networked control systems are derived and transformed to a feasibility problem of linear matrix inequality formulation, which can be solved by the Matlab LMI toolbox, and the feasible solutions provide the maximum allowable delay bound that makes the system stable. A numerical example is provided, which shows that the analysis method is valid and the stability criteria are feasible.

For several superior controllers of the first-order integrating processes with long delay, the windup problems are analyzed in detail when the control signal saturates. The results show that these controllers have similar characteristics about the process input limitation. And then, a simple and effective anti-windup scheme, without an additional parameter, is designed for these controllers. Simulations run with three main controllers, and the results illustrate that the proposed method may achieve good performance under the nominal and model uncertainty cases.

The exponential stability is investigated for a class of continuous time linear systems with a finite state Markov chain form process and the impulsive jump at switching moments. The conditions, based on the average dwell time and the ratio of expectation of the total time running on all unstable subsystems to the expectation of the total time running on all stable subsystems, assure the exponential stability with a desired stability degree of the system irrespective of the impact of impulsive jump. The uniformly bounded result is realized for the case in which switched system is subjected to the impulsive effect of the excitation signal at some switching moments.

frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno (T-S) fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.

The stability and stabilization of a class of linear switched time-varying delay systems are investigated. A piecewise quadratic Lyapunov function (PWQLF) is constructed and is used to obtain the stability conditions based on the linear matrix inequalities (LMIs). The stabilizing controller for this class of system is then designed and the solution of the desired controller can be obtained by a cone complementary linearization algorithm. Numerical examples are provided to illustrate the less conservativeness of the new stability and the validity of the controller design procedures.

In order to improve the filter accuracy for the nonlinear error model of strapdown inertial navigation system (SINS) alignment, Unscented Kalman Filter (UKF) is presented for simulation with stationary base and moving base of SINS alignment. Simulation results show the superior performance of this approach when compared with classical suboptimal techniques such as extended Kalman filter in cases of large initial misalignment. The UKF has good performance in case of small initial misalignment.

In practice, gain perturbations of controllers which are caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.

Under dense urban fading environment, performance of joint multi-path parameter estimation method based on traditional point signal model degrades seriously. In this paper, a new space and time signal model based on multipath distribution function is given after new space and time manifold is reconstructed. Then joint spacetime signal subspace is obtained by converting acquired channel from time domain to frequency domain .Then space and time spectrum is formulated by the space sub-matrix and time sub-matrix taken out of joint space-time signal subspace, and parameters are estimated by searching the minimum eigenvalues of the space matrix and the time matrix. Lastly, A space and time parameters matching process is performed by using the orthogonal property between joint noise subspace and the space-time manifold. In contrast with tradition MUSIC, the algorithm we present here only need two 1- dimension searching and was not sensitive to different distribution function.

A modification of Horn and Schunk’s approach is investigated, which leads to a better preservation of flow discontinuities. It improves Horn–Schunk model in three aspects: (1) It replaces the smooth weight coefficient in the energy equation by the variable weight coefficient. (2) It adopts a novel method to compute the mean velocity. The novel method also reflects the effect of the intensity difference on the image velocity diffusion. (3) It introduces a more efficient iterative method than the Gauss–Seidel method to solve the associated Euler–Lagrange equation. The experiment results validate the better effect of the improved method on preserving discontinuities.

To solve the problems of SVM in dealing with large sample size and asymmetric distributed samples, a support vector classification algorithm based on variable parameter linear programming is proposed. In the proposed algorithm, linear programming is employed to solve the optimization problem of classification to decrease the computation time and to reduce its complexity when compared with the original model. The adjusted punishment parameter greatly reduced the classification error resulting from asymmetric distributed samples and the detailed procedure of the proposed algorithm is given. An experiment is conducted to verify whether the proposed algorithm is suitable for asymmetric distributed samples.

A quality of service (QoS) or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path (MCP) problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.

The key problem of the adaptive mixture background model is that the parameters can adaptively change according to the input data. To address the problem, a new method is proposed. Firstly, the recursive equations are inferred based on the maximum likelihood rule. Secondly, the forgetting factor and learning rate factor are redefined, and their still more general formulations are obtained by analyzing their practical functions. Lastly, the convergence of the proposed algorithm is proved to enable the estimation converge to a local maximum of the data likelihood function according to the stochastic approximation theory. The experiments show that the proposed learning algorithm excels the formers both in converging rate and accuracy.

The novel information criterion (NIC) algorithm can find the principal subspace quickly, but it is not an actual principal component analysis (PCA) algorithm and hence it cannot find the orthonormal eigen-space which corresponds to the principal component of input vector. This defect limits its application in practice. By weighting the neural network’s output of NIC, a modified novel information criterion (MNIC) algorithm is presented. MNIC extractes the principal components and corresponding eigenvectors in a parallel online learning program, and overcomes the NIC’s defect. It is proved to have a single global optimum and nonquadratic convergence rate, which is superior to the conventional PCA online algorithms such as Oja and LMSER. The relationship among Oja, LMSER and MNIC is exhibited. Simulations show that MNIC could converge to the optimum fast. The validity of MNIC is proved.

A new algorithm is proposed for completing the missing parts caused by the removal of foreground or background elements from an image of natural scenery in a visually plausible way. The major contributions of the proposed algorithm are: (1) for most natural images, there is a strong orientation of texture or color distribution. So a method is introduced to compute the main direction of the texture and complete the image by limiting the search to one direction to carry out image completion quite fast; (2) there exists a synthesis ordering for image completion. The searching order of the patches is defined to ensure the regions with more known information and the structures should be completed before filling in other regions; (3) to improve the visual effect of texture synthesis, an adaptive scheme is presented to determine the size of the template window for capturing the features of various scales. A number of examples are given to demonstrate the effectiveness of the proposed algorithm.

To investigate the judging problem of optimal dividing matrix among several fuzzy dividing matrices in fuzzy dividing space, correspondingly, which is determined by the various choices of cluster samples in the totality sample space, two algorithms are proposed on the basis of the data analysis method in rough sets theory: information system discrete algorithm (algorithm 1) and samples representatives judging algorithm (algorithm 2). On the principle of the farthest distance, algorithm 1 transforms continuous data into discrete form which could be transacted by rough sets theory. Taking the approximate precision as a criterion, algorithm 2 chooses the sample space with a good representative. Hence, the clustering sample set in inducing and computing optimal dividing matrix can be achieved. Several theorems are proposed to provide strict theoretic foundations for the execution of the algorithm model. An applied example based on the new algorithm model is given, whose result verifies the feasibility of this new algorithm model.

The solution of distributed mutual exclusion is difficult in Ad hoc networks owing to dynamic topologies and mobility. Based on the analysis of the properties of Ad hoc networks and the disadvantages of the traditional algorithms, an improved Ad hoc system model was given and a novel algorithm was presented as AHDME (Ad Hoc Distributed Mutual Exclusion); it was based on the token-asking algorithms. It utilized broadcast to search for the token and to decrease the message complexity of multi-hop Ad hoc networks. Lamport’s timestamp was improved to ensure the time sequence and to prevent nodes from starvation. When compared to traditional algorithms, AHDME does not require the fixed size of request queues and the global system information, which adapts itself to the frequent arrival/departures and the limited computing capability of nodes in Ad hoc networks. Performance analysis and simulation results show that the AHDME algorithm has low message complexity, small space complexity, and short response delay.

The security of certain classes of the generalized self-shrinking sequence (GSS) generators is analyzed. Firstly, it is shown that the security of these GSS generators is equivalent to the security of the GSS generators of the class-1, after which two effective key recovery attacks on the GSS generators of the class-1 are developed to evaluate their security.

Multiple QoS modeling and algorithm in grid system is considered. Grid QoS requirements can be formulated as a utility function for each task as a weighted sum of its each dimensional QoS utility functions. Multiple QoS constraint resource scheduling optimization in computational grid is distributed to two subproblems: optimization of grid user and grid resource provider. Grid QoS scheduling can be achieved by solving sub problems via an iterative algorithm.

Enterprise application integration (EAI) focuses on the collaboration and interconnection of various information systems, so the basic problem to be solved is how EAI guarantees that the applications will produce consistent presentation of data, message and transaction. The metadata methodology may give us certain good ideas. First, the metadata description method of manufacturing information resource, transaction process and message delivery is put forward on the basis of operation analysis of manufacturing-oriented EAI, and then the tree-structured XML schema of corresponding object is built and a framework of metadata application in the discrete Manufacturing-Oriented EAI is established. Finally, a practical enterprise information integration system in Shanghai Tobacco Machine Co., Ltd. is presented as an example to show how it functions.

It is well known that the algebraic expression of AES S-box is very simple and only 9 terms are involved. Hence, AES security is suspected although there is no vulnerability on it so far. To eliminate the weakness of extremely small terms in the algebraic expression of AES S-box, one improved AES S-box is proposed, which preserves the algebraic degree invariable but significantly increases the number of its algebraic expression terms from 9 to 255. At the same time, Boolean function has good characters in balance and strict avalanche criterion (SAC), etc. Finally, it is proved that the improved AES S-box scheme is secure against the powerful known differential and linear cryptanalysis.

Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit. The feature evaluation and extraction methods based on neural network are presented. Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently. The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis efficiency. A fault diagnosis illustration validated this method.