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Systems Engineering and Electronics, Journal of

Issue 3 • Date Sept. 2006

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Displaying Results 1 - 25 of 44
  • [Front cover]

    Page(s): c1
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    Freely Available from IEEE
  • Copyright page

    Page(s): 1
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  • Contents

    Page(s): 1 - 2
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  • Characteristics and realization of the second generation surface acoustic wave's wavelet device

    Page(s): 467 - 472
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1874 KB)  

    To overcome the bulk acoustic wave (BAW), the triple transit signals and the discontinuous frequency band in the first generation surface acoustic wave's (FGSAW's) wavelet device, the full transfer multistrip coupler (MSC) is applied to implement wavelet device, and a novel structure of the second generation surface acoustic wave's (SGSAW's) wavelet device is proposed. In the SGSAW's wavelet device, the BAW is separated and eliminated in different acoustic propagating tracks, and the triple transit signal is suppressed. For arbitrary wavelet scale device, the center frequency is three times the radius of frequency band, which ensures that the frequency band of the SGSAW's wavelet device is continuous, and avoids losing signals caused by the discontinuation of frequency band. Experimental result confirms that the BAW suppression, ripples in band, receiving loss and insertion loss of the SGSAW's wavelet device are remarkably improved compared with those of the FGSAW's wavelet device. View full abstract»

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  • Target tracking based on frequency spectrum amplitude

    Page(s): 473 - 476
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (713 KB)  

    The amplitude of frequency spectrum can be integrated with probabilistic data association (PDA) to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algorithm is presented which adopts the amplitude of frequency spectrum to improve target tracking in clutter. The probabilistic density distribution of frequency spectrum amplitude is analyzed. By simulation, the results show that the algorithm is superior to PDA. This approach enhances stability for the association probability and increases the performance of target tracking. View full abstract»

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  • Research on a novel restoration algorithm of turbulence-degraded images with alternant iterations

    Page(s): 477 - 482
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1934 KB)  

    A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images. Based on the double loops, the iterative relations for estimating the turbulent point spread function PSF and object image alternately are derived. The restoration experiments have been made on computers, showing that the proposed algorithm can obtain the optimal estimations of the object and the point spread function, with the feasibility and practicality of the proposed algorithm being convincing. View full abstract»

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  • Efficient structures for wideband digital receiver

    Page(s): 483 - 486
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (908 KB)  

    Digital receivers have become more and more popular in radar, communication, and electric warfare for the advantages compared with their analog counterparts. But conventional digital receivers have been generally considered impractical for bandwidth greater than several hundreds MHz. To extend receiver bandwidth, decrease data rate and save hardware resources, three novel structures are proposed. They decimate the data stream prior to mixing and filtering, then process the multiple decimated streams in parallel at a lower rate. Consequently it is feasible to realize wideband receivers on the current ASIC devices. A design example and corresponding simulation results are demonstrated to evaluate the proposed structures. View full abstract»

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  • Dynamic weighted voting for multiple classifier fusion: A generalized rough set method

    Page(s): 487 - 494
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    To improve the performance of multiple classifier system, a knowledge discovery based dynamic weighted voting (KD-DWV) is proposed based on knowledge discovery. In the method, all base classifiers may be allowed to operate in different measurement/feature spaces to make the most of diverse classification information. The weights assigned to each output of a base classifier are estimated by the separability of training sample sets in relevant feature space. For this purpose, some decision tables (DTs) are established in terms of the diverse feature sets. And then the uncertainty measures of the separability are induced, in the form of mass functions in Dempster-Shafer theory (DST), from each DTs based on generalized rough set model. From the mass functions, all the weights are calculated by a modified heuristic fusion function and assigned dynamically to each classifier varying with its output. The comparison experiment is performed on the hyperspectral remote sensing images. And the experimental results show that the performance of the classification can be improved by using the proposed method compared with the plurality voting (PV). View full abstract»

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  • Uncertain information fusion with robust adaptive neural networks-fuzzy reasoning

    Page(s): 495 - 501
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1408 KB)  

    In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself (including fuzziness, randomness, incompleteness as well as roughness, etc). Hence it requires investigating the problem of uncertain information fusion. Robust learning algorithm which adapts to complex environment and the fuzzy inference algorithm which disposes fuzzy information are explored to solve the problem. Based on the fusion technology of neural networks and fuzzy inference algorithm, a multi-sensor uncertain information fusion system is modeled. Also RANFIS learning algorithm and fusing weight synthesized inference algorithm are developed from the ANFIS algorithm according to the concept of robust neural networks. This fusion system mainly consists of RANFIS confidence estimator, fusing weight synthesized inference knowledge base and weighted fusion section. The simulation result demonstrates that the proposed fusion model and algorithm have the capability of uncertain information fusion, thus is obviously advantageous compared with the conventional Kalman weighted fusion algorithm. View full abstract»

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  • IAE-adaptive Kalman filter for INS/GPS integrated navigation system

    Page(s): 502 - 508
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1804 KB)  

    A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel's altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter (SKF) assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering (IAE-AKF) algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAE-AKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstrated that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter. View full abstract»

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  • Blind channel identication of nonlinear folding mixing model

    Page(s): 509 - 512
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (586 KB)  

    Signals from multi-sensor systems are often mixtures of (statistically) independent sources by unknown mixing method. Blind source separation(BSS) and independent component analysis(ICA) are the methods to identify/recover the channels and the sources. BSS/ICA of nonlinear mixing models are difficult problems. For instance, the post-nonlinear model has been studied by several authors. It is noticed that in most cases, the proposed models are always with an invertible mixing. According to this fact there is an interesting question: how about the situation of the non-invertible non-linear mixing in BSS or ICA? A new simple non-linear mixing model is proposed with a kind of non-invertible mixing, the folding mixing, and method to identify its channel, blindly. View full abstract»

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  • Novel Satellite Transport Protocol with on-board spoofing proxy

    Page(s): 513 - 520
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1401 KB)  

    As a result of the exponential growing rate of worldwide Internet usage, satellite systems are required to support broadband Internet applications. The transmission control protocol (TCP) which is widely used in the Internet, performs very well on wired networks. However, in the case of satellite channels, due to the delay and transmission errors, TCP performance degrades significantly and bandwidth of satellite links can not be fully utilized. To improve the TCP performance, a new idea of placing a TCP spoofing proxy in the satellite is considered. A Novel Satellite Transport Protocol (NSTP) which takes advantage of the special properties of the satellite channel is also proposed. By using simulation, as compared with traditional TCPs, the on-board spoofing proxy integrated with the special transport protocol can significantly enhance throughput performance on the high BER satellite link, the time needed to transfer files and the bandwidth used in reverse path are sharply reduced. View full abstract»

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  • Wavelet neural network based fault diagnosis in nonlinear analog circuits

    Page(s): 521 - 526
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    The theories of diagnosing nonlinear analog circuits by means of the transient response testing are studied. Wavelet analysis is made to extract the transient response signature of nonlinear circuits and compress the signature dada. The best wavelet function is selected based on the between-category total scatter of signature. The fault dictionary of nonlinear circuits is constructed based on improved back-propagation(BP) neural network. Experimental results demonstrate that the method proposed has high diagnostic sensitivity and fast fault identification and deducibility. View full abstract»

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  • Application of uniform DFT filter bank in radar jamming system

    Page(s): 527 - 530
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (830 KB)  

    The principle of uniform DFT filter bank is presented. Exploiting poly-phase structure, radar jamming system samples the intercepted wideband radar signals through analysis filter bank by different channels and linearly modulates the intercepted radar signal according to the theory of signal and system, then synthesizes the jamming signal through the synthesis filter bank. The method merely requires lower sample frequency, reduces the computational complexity and the data quantity to be processed. The un-ideal filter's influence to the result of signals processing is analyzed by simulating the match filter in radar jamming system. View full abstract»

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  • Sensor management based on fisher information gain

    Page(s): 531 - 534
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (721 KB)  

    Multi-sensor system is becoming increasingly important in a variety of military and civilian applications. In general, single sensor system can only provide partial information about environment while multi-sensor system provides a synergistic effect, which improves the quality and availability of information. Data fusion techniques can effectively combine this environmental information from similar and/or dissimilar sensors. Sensor management, aiming at improving data fusion performance by controlling sensor behavior, plays an important role in a data fusion process. This paper presents a method using fisher information gain based sensor effectiveness metric for sensor assignment in multi-sensor and multi-target tracking applications. The fisher information gain is computed for every sensor-target pairing on each scan. The advantage for this metric over other ones is that the fisher information gain for the target obtained by multi-sensors is equal to the sum of ones obtained by the individual sensor, so standard transportation problem formulation can be used to solve this problem without importing the concept of pseudo sensor. The simulation results show the effectiveness of the method. View full abstract»

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  • Evolution of two properties for scale-free network

    Page(s): 535 - 540
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    Fitness of node can denote its competing power and clustering denotes the transitivity of network. Because the fitness of node is uncertain or fuzzy in some social networks, an explicit form of the degree distribution on fuzzy fitness is derived within a mean field approach. It is a weighted sum of different fuzzy fitness. It can be found that the fuzzy fitness of nodes may lead to multiscaling. Moreover, the clustering coefficient of node decays as power law and clustering coefficient of network behavior not-decrease-but-increase' phenomenon after some time. Some computer simulation results of these models illustrate these analytical results. View full abstract»

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  • Novel algorithm for constructing support vector machine regression ensemble

    Page(s): 541 - 545
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1031 KB)  

    A novel algorithm for constructing support vector machine regression ensemble is proposed. As to regression prediction, support vector machine regression (SVMR) ensemble is proposed by resampling from given training data sets repeatedly and aggregating several independent SVMRs, each of which is trained to use a replicated training set. After training, several independently trained SVMRs need to be aggregated in an appropriate combination manner. Generally, the linear weighting is usually used like expert weighting score in Boosting Regression and it is without optimization capacity. Three combination techniques are proposed, including simple arithmetic mean, linear least square error weighting and nonlinear hierarchical combining that uses another upper-layer SVMR to combine several lower-layer SVMRs. Finally, simulation experiments demonstrate the accuracy and validity of the presented algorithm. View full abstract»

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  • Multi-criteria classification approach with polynomial aggregation function and incomplete certain information

    Page(s): 546 - 550
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    The relationship between the importance of criterion and the criterion aggregation function is discussed, criterion's weight and combinational weights between some criteria are defined, and a multi-criteria classification method with incomplete certain information and polynomial aggregation function is proposed. First, linear programming is constructed by classification to reference alternative set (assignment examples) and incomplete certain information on criterion's weights. Then the coefficient of the polynomial aggregation function and thresholds of categories are gained by solving the linear programming. And the consistency index of alternatives is obtained, the classification of the alternatives is achieved. The certain criteria's values of categories and uncertain criteria's values of categories are discussed in the method. Finally, an example shows the feasibility and availability of this method. View full abstract»

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  • Remarks on a benchmark nonlinear constrained optimization problem

    Page(s): 551 - 553
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (474 KB)  

    Remarks on a benchmark nonlinear constrained optimization problem are made. Due to a citation error, two absolutely different results for the benchmark problem are obtained by independent researchers. Parallel simulated annealing using simplex method is employed in our study to solve the benchmark nonlinear constrained problem with mistaken formula and the best-known solution is obtained, whose optimality is testified by the Kuhn-Tucker conditions. View full abstract»

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  • Dual worth trade-off method and its application for solving multiple criteria decision making problems

    Page(s): 554 - 558
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (745 KB)  

    To overcome the limitations of the traditional surrogate worth trade-off (SWT) method and solve the multiple criteria decision making problem more efficiently and interactively, a new method labeled dual worth tradeoff (DWT) method is proposed. The DWT method dynamically uses the duality theory related to the multiple criteria decision making problem and analytic hierarchy process technique to obtain the decision maker's solution preference information and finally find the satisfactory compromise solution of the decision maker. Through the interactive process between the analyst and the decision maker, trade-off information is solicited and treated properly, the representative subset of efficient solutions and the satisfactory solution to the problem are found. The implementation procedure for the DWT method is presented. The effectiveness and applicability of the DWT method are shown by a practical case study in the field of production scheduling. View full abstract»

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  • Survey of the research on dynamic weapon-target assignment problem

    Page(s): 559 - 565
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    The basic concepts and models of weapon-target assignment (WTA) are introduced and the mathematical nature of the WTA models is also analyzed. A systematic survey of research on WTA problem is provided. The present research on WTA is focused on models and algorithms. In the research on models of WTA, the static WTA models are mainly studied and the dynamic WTA models are not fully studied in deed. In the research on algorithms of WTA, the intelligent algorithms are often used to solve the WTA problem. The small scale of static WTA problems has been solved very well, however, the large scale of dynamic WTA problems has not been solved effectively so far. Finally, the characteristics of dynamic WTA are analyzed and directions for the future research on dynamic WTA are discussed. View full abstract»

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  • Selection of the best initial orbital elements of satellite based on fuzzy integration evaluation method

    Page(s): 566 - 570
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (870 KB)  

    The fuzzy integration evaluation method (FIEM) is studied in order to select the best orbital elements from the multi-group initial orbits determined by a satellite TT&C (Tracking, Telemetry and Control) center with all kinds of data sources. By employing FIEM together with the experience of TT&C experts, the index system to evaluate the selection of the best initial orbits is established after the data sources and orbit determination theories are studied. Besides, the concrete steps in employing the method are presented. Moreover, by taking the objects to be evaluated as evaluation experts, the problem of how to generate evaluation matrices is solved. Through practical application, the method to select the best initial orbital elements has been proved to be flexible and effective. The originality of the method is to find a new evaluation criterion (comparing the actually tracked orbits) replacing the traditional one (comparing the nominal orbits) for selecting the best orbital elements. View full abstract»

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  • Robust H control for uncertain descriptor systems with state and control delay

    Page(s): 571 - 575
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (724 KB)  

    The problem of robust stabilization for uncertain continuous descriptor system with state and control delay is considered. The time-varying parametric uncertainty is assumed to be norm-bounded. The purpose of the robust stabilization is to design a memoryless state feedback law such that the resulting closed-loop system is robustly stable. A sufficient condition that uncertain continuous descriptor system is robustly stabilizabled by state feedback law is derived in terms of linear matrix inequality (LMI). Finally, a numerical example is provided to demonstrate the application of the proposed method. View full abstract»

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  • Sliding mode H control for a class of uncertain nonlinear state-delayed systems

    Page(s): 576 - 585
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1324 KB)  

    A new proportional-integral (PI) sliding surface is designed for a class of uncertain nonlinear state-delayed systems. Based on this, an adaptive sliding mode controller (ASMC) is synthesized, which guarantees the occurrence of sliding mode even when the system is undergoing parameter uncertainties and external disturbance. The resulting sliding mode has the same order as the original system, so that it becomes easy to solve the H control problem by designing a memoryless H state feedback controller. A delay-dependent sufficient condition is proposed in terms of linear matrix inequalities (LMIs), which guarantees the sliding mode robust asymptotically stable and has a noise attenuation level γ in an H sense. The admissible state feedback controller can be found by solving a sequential minimization problem subject to LMI constraints by applying the cone complementary linearization method. This design scheme combines the strong robustness of the sliding mode control with the H norm performance. A numerical example is given to illustrate the effectiveness of the proposed scheme. View full abstract»

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  • Block and parallel modelling of broad domain nonlinear continuous mapping based on NN

    Page(s): 586 - 592
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    The necessity of the use of the block and parallel modeling of the nonlinear continuous mappings with NN is firstly expounded quantitatively. Then, a practical approach for the block and parallel modeling of the nonlinear continuous mappings with NN is proposed. Finally, an example indicating that the method raised in this paper can be realized by suitable existed software is given. The results of the experiment of the model discussed on the 3-D Mexican straw hat indicate that the block and parallel modeling based on NN is more precise and faster in computation than the direct ones and it is obviously a concrete example and the development of the large-scale general model established by Tu Xuyan. View full abstract»

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Aims & Scope

Journal of Systems Engineering and Electronics reports the latest developments and achievements in both theoretical and practical aspects of systems engineering, electronics and related research areas.

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Editor-in-Chief
Professor Rong Shi
Journal of Systems Engineering and Electronics