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Systems Engineering and Electronics, Journal of

Issue 3 • Date Sept. 2004

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Displaying Results 1 - 25 of 42
  • [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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  • Multiuser detector based on wavelet networks

    Page(s): 225 - 231
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1172 KB)  

    Multiple access interference (MAI) and near-far problem are two major obstacles in DS-CDMA systems. Combining wavelet neural networks and two matched filters, the novel multiuser detector, which is based on multiple variable function estimation wavelet networks over single path asynchronous channel and space-time channel respectively is presented. Excellent localization characteristics of wavelet functions in both time and frequency domains allowed hierarchical multiple resolution learning of input-output data mapping. The mathematic frame of the neural networks and error back ward propagation algorithm are introduced. The complexity of the multiuser detector only depends on that of wavelet networks. With numerical simulations and performance analysis, it indicates that the multiuser detector has excellent performance in eliminating MAI and near-far resistance. View full abstract»

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  • Analysis of linear weighted order statistics CFAR algorithm

    Page(s): 232 - 236
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    CFAR technique is widely used in radar targets detection fields. Traditional algorithm is cell averaging (CA), which can give a good detection performance in a relatively ideal environment. Recently, censoring technique is adopted to make the detector perform robustly. Ordered statistic (OS) and trimmed mean (TM) methods are proposed. TM methods treat the reference samples which participate in clutter power estimates equally, but this processing will not realize the effective estimates of clutter power. Therefore, in this paper a quasi best weighted (QBW) order statistics algorithm is presented. In special cases, QBW reduces to CA and the censored mean level detector (CMLD). View full abstract»

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  • Turbo decoding using two soft output values

    Page(s): 237 - 240
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (756 KB)  

    It is well known that turbo decoding always begins from the first component decoder and supposes that the apriori information is “0” at the first iterative decoding. To alternatively start decoding at two component decoders, we can gain two soft output values for the received observation of an input bit. It is obvious that two soft output values comprise more sufficient extrinsic information than only one output value obtained in the conventional scheme since different start points of decoding result in different combinations of the a priori information and the input codewords with different symbol orders due to the permutation of an interleaver. Summarizing two soft output values for erery bit before making hard decisions, we can correct more errors due to their complement. Consequently, turbo codes can achieve better error correcting performance than before in this way. Simulation results show that the performance of turbo codes using the novel proposed decoding scheme can get a growing improvement with the increment of SNR in general compared to the conventional scheme. When the bit error probability is 10−5, the proposed scheme can achieve 0.5 dB asymptotic coding gain or so under the given simulation conditions. View full abstract»

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  • Study on the evaluation of aerospace microelectronic industry

    Page(s): 241 - 247
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    Aerospace microelectronic technology has become the core competence of aerospace technology. For evaluating the aerospace microelectronic industry, it is necessary to change descriptive language of goal to quantitative index that can be measured. Knowing quantified goals or tree structure and array of general goal system, with certain algorithm and processing each corresponding list or array, we can bring out a quantified general goal value. The multi-objective (multi-attribute) evaluation method and the relevant weight sum algorithm have been adopted to quantitatively evaluate and forecast the developing state of the industry. A practical example illustrates that the applied decision technique and the algorithm are feasible and effective. View full abstract»

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  • Cipher quasi-chaotic code for frequency hopping communications

    Page(s): 248 - 256
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1608 KB)  

    The chaotic frequency hopping (FH) communication systems have been presented so far. The chaotic sequences possesses good randomness and sensitive dependence on initial conditions, which is quite advantageous to run the FH codes in code-division multiple access (CDMA) systems. But the finite precision of computation and the fact of the low-dimensional chaos predicted easily cause difficulty in chaotic application. In this paper, some disadvantages associatedwith the conventional FH codes and the chaotic code scrambled by m-sequences are reviewed briefly. In order to overcome these drawbacks to some extents, a new higher performance FH code called cipher quasi-chaotic (CQC) code is proposed, which is generated by combining the clock-controlled stream cipher technique and chaotic dynamics. Performance analysis applying in FH communication systems of this kind of code is given. The privacy of the CQC sequence is also analyzed. View full abstract»

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  • Improved fuzzy identification method based on Hough transformation and fuzzy clustering

    Page(s): 257 - 261
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (807 KB)  

    This paper presents an approach that is useful for the identification of a fuzzy model in SISO system. The initial values of cluster centers are identified by the Hough transformation, which considers the linearity and continuity of given input-output data, respectively. For the premise parts parameters identification, we use fuzzy-C-means clustering method. The consequent parameters are identified based on recursive least square. This method not only makes approximation more accurate, but also let computation be simpler and the procedure is realized more easily. Finally, it is shown that this method is useful for the identification of a fuzzy model by simulation. View full abstract»

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  • Novel clutter map CFAR algorithm with amplitude limiter

    Page(s): 262 - 265
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (616 KB)  

    The traditional clutter map constant false alarm rate (CM-CFAR) detector is affected by interference and self-masking[1] which will cause the low probability of detection. To solve these problems, a novel algorithm named clutter map CFAR with amplitude limiter (ALCM-CFAR) is proposed, in which the amplitude of the input signal is limited by a filter. The simulation results prove the effectiveness of ALCM-CFAR algorithm. View full abstract»

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  • Joint channel estimation and symbol detection for space-time block code

    Page(s): 266 - 269
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (671 KB)  

    The simplified joint channel estimation and symbol detection based on the EM (expectation-maximization) algorithm for space-time block code (STBC) are proposed. By assuming channel to be invariant within only one STBC word and utilizing the orthogonal structure of STBC, the computational complexity and cost of this algorithm are both very low, so it is very suitable to implementation in real systems. View full abstract»

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  • Identification of linear continuous-time system using wavelet modulating filters

    Page(s): 270 - 277
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1158 KB)  

    An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filters have been analyzed. Using linear modulating filters, we can obtain an identification model that is parameterized directly in continuous-time model parameters. By applying the results from discrete-time model identification to the obtained identification model, a continuous-time estimation method is developed. Considering the accuracy of parameter estimates, an instrumental variable (IV) method is proposed, and the design of modulating integral filter is discussed. The relationship between the accuracy of identification and the parameter of modulating filter is investigated, and some points about designing Gaussian wavelet modulating function are outlined. Finally, a simulation study is also included to verify the theoretical results. View full abstract»

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  • Hybrid chaotic sequence for QS-CDMA system with RAKE receiver

    Page(s): 278 - 282
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    A class of the hybrid chaotic sequences is presented. The generator of the sequences is given and realized by the digital method. The hybrid chaotic sequences exhibit good random properties that are very important for the pefformance of QS-CDMA system with RAKE receiver. The performance of the system is analyzed when the hybrid chaotic sequences are used as spreading codes in a QS-CDMA system with RAKE receiver and compared with those obtained for m-sequences and logistic sequences. The results show that the hybrid chaotic sequences are a class of very promising spreading codes for QS-CDMA system. View full abstract»

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  • Complex fitting 3D closed-form Green's function and its application for silicon RF IC's

    Page(s): 283 - 287
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (841 KB)  

    An approximate three-dimensional closed-form Green's function with the type of exponential function is derived over a lossy multilayered substrate by means of the Fourier transforms and a novel complex fitting approach. This Green's function is used to extract the capacitance matrix for an arbitrary three-dimensional arrangement of conductors located anywhere in the silicon IC substrate. Using this technique, the substrate loss in silicon integrated circuits can be analyzed. An example of inductor modeling is presented to show that the technique is quite effective. View full abstract»

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  • Observer-based fault detection scheme for a class of discrete time-delay systems

    Page(s): 288 - 294
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    In this contribution, robust fault detection problems for discrete time-delay systems with l2-norm bounded unknown inputs are studied. The basic idea of our study is first to introduce a state-memoryless observer-based fault detection filter (FDF) as the residual generator and then to formulate such a FDF design problem as an H optimization problem in the sense of increasing the sensitivity of residual to the faults, while simultaneously enhancing the robustness of residual to unknown input as well as plant input. The main results consist of the formulation of such a residual generation optimization problem, solvability conditions and the derivation of an analytic solution. The residual evaluation problem is also considered, which includes the determination of residual evaluation function and threshold. A numerical example is used to demonstrate the proposed fault detection scheme. View full abstract»

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  • Improvement on GM models

    Page(s): 295 - 298
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    Since grey system theory was established by prof. Deng, GM models and their improvements have all taken the first vector of the original sequence as the initialization, which resulted to deficiency in making use of the latest information. Based on the principle, which new information should be used fully, we think it is scientific to pay more attention to the new information or endow them a more weigh. So, this paper deals with the GM improvement by taking the n-th vector as the initialization, and gets great improvement in forecasting precision. Last, we validate the practicability and reliability of the models with examples. View full abstract»

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  • Hybrid approach for fuzzy system design

    Page(s): 299 - 303
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    A hybrid approach for fuzzy system design based on clustering and a kind of neurofuzzy networks is proposed. An unsupervised clustering technique is firstly used to determine the number of if-then fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Then, a class of neurofuzzy networks is constructed and its weights are tuned so that the obtained fuzzy rule base has a high accuracy. Finally, two examples of function approximation problems are given to illustrate the effectiveness of the proposed approach. View full abstract»

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  • Neural adaptive sliding mode speed tracking control of a DC motor

    Page(s): 304 - 308
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (741 KB)  

    We propose a BPNN based adaptive sliding mode control scheme for speed tracking of a DC motor with unknown system nonlinearities. The input-output linearization technique is used to cancel the nonlinearities, and output of the BPNN is incorporated into the controller in the proposed scheme. It is shown that the rotor speed of a DC motor can follow any arbitrarily selected trajectories under variable load torque. Then the application of the approach is tested via some simulations. View full abstract»

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  • Primary safe criterion of earth-brushing flight for flying vehicle over digital surface model

    Page(s): 309 - 314
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    In modern terrain-following guidance it is an important index for flight vehicle to cruise about safely and normally. On the basis of a constructing method of digital surface model (DSM), the definition, classification and scale analysis of an isolated obstacle threatening flight safety of terrain-following guidance are made. When the interval of verticaland cross-sections on DSM is 12.5 m, the proportion of isolated obstacles to the data amount of DSM model to be loaded is optimal. The main factors influencing the lowest flying height in terrain-following guidance are analyzed, and a primary safe criterion of the lowest flying height over DSM model is proposed. According to their testerrors, the lowest flying height over 1:10 000 DSM model can reach 40.5 m∼ 45.0 m in terrain-following guidance. It is shown from the simulation results of a typical urban district that the proposed models and methods are reasonable and feasible. View full abstract»

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  • ERBF network with immune clustering

    Page(s): 315 - 318
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (802 KB)  

    Based on immune clustering and evolutionary programming(EP), a hybrid algorithm to train the RBF network is proposed. An immune fuzzy C-means clustering algorithm (IFCM) is used to adaptively specifythe amount and initial positions of the RBF centers according to input data set; then the RBF network is trained with EP that tends to globaloptima. The application of the hybrid algorithm in multiuser detection problem demonstrates that the RBF network trained with the algorithm has simple network structure with good generalization ability. View full abstract»

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  • Approximation methods of mixed l1/H2 optimization problems for MIMO discrete-time systems

    Page(s): 319 - 326
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    The mixed l1/H2 optimization problem for MIMO (multiple input-multiple output) discrete-time systems is considered. This problem is formulated as minimizing the l1-norm of a closed-loop transfer matrix while maintaining the H2-norm of another closed-loop transfer matrix at prescribed level. The continuity property ofthe optimal value in respect to changes in the H2-norm constraint is studied. The existence of the optimal solutions of mixed l1/H2 problem is proved. Because the solution of the mixed l1/H2 problem is based on the scaled-Q method, it avoids the zero interpolation difficulties. The convergent upper and lower bounds can be obtained by solving a sequence of finite dimensional nonlinear programming for which many efficient numerical optimization algorithms exist. View full abstract»

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  • Autonomous orbit determination for the probe around small body

    Page(s): 327 - 332
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1041 KB)  

    The algorithm of autonomous orbit determination for the probe around small body is studied. In the algorithm, first,” the observed images of the body are compared with its pre-computed model of the body to obtain the location of the limb features of the body in the inertial coordinate. Second, the information of the images and features in utilized to obtain the position of the probe using the Levenberg-Marquardt algorithm. The position is then input to an extended Kalman filter which determines the real time orbit of the probe. Finally, considering the effective of the irregular small body shape perturbation and the small body model parameter error on the orbit determination precise, the procedure of autonomous orbit determination is validated using digital simulation. View full abstract»

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  • PI tuning for large dead-time processes with a new robustness specification

    Page(s): 333 - 336
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (597 KB)  

    A simple PI controller tuning method for large dead-time processes is presented. First, a first-order plus deadtime model is identified on the basis of relay feedback experiments, which Nyquist curve is very close to that of large dead-time processes over a wide frequency range. With the model available, PI controller is designed with a new robust specification. Simulation examples show the effectiveness and feasibility of the presented PI tuning method for large dead-time processes. View full abstract»

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  • Robust stability test for 2-D continuous-discrete systems with interval parameters

    Page(s): 337 - 343
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    It is revealed that the dynamic stability of 2-D recursive continuous-discrete systems with interval parameters involves the problem of robust Hurwitz-Schur stability of bivariate polynomials family. It is proved that the Hurwitz Schur stability of the denominator polynomials of the systems is necessary and sufficient for the asymptotic stability of the 2-D hybrid systems. The 2-D hybrid transformation, i.e. 2-D Laplace-Z transformation, has beenproposed to solve the stability analysis of the 2-D continuous-discrete systems, to get the 2-D hybrid transfer functions of the systems. The edge test for the Hurwitz-Schur stability of interval bivariate polynomials is introduced. The Hurwitz-Schur stability of the interval family of 2-D polynomials can be guaranteed by the stability of its finite edge polynomials of the family. An algorithm about the stability test of edge polynomials is given. View full abstract»

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  • Global exponential stability for delayed cellular neural networks and estimate of exponential convergence rate

    Page(s): 344 - 349
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (837 KB)  

    Some sufficient conditions for the global exponential stability and lower bounds on the rate of exponential convergence of the cellular neural networks with delay (DCNNs) are obtained by means of a method based on delay differential inequality. The method, which does not make use of any Lyapunov functionals, is simple and valid for the stability analysis of neural networks with delay. Some previously established results in this paper are shown to be special casses of the presented result. View full abstract»

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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