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Systems Engineering and Electronics, Journal of

Issue 6 • Date Dec. 2010

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Displaying Results 1 - 25 of 32
  • [Front cover]

    Publication Year: 2010 , Page(s): c1
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  • Copyright page

    Publication Year: 2010 , Page(s): 1
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  • Instructions for authors

    Publication Year: 2010 , Page(s): 1
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  • Contents

    Publication Year: 2010 , Page(s): 1 - 2
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  • Low complexity DCT-based distributed source coding with Gray code for hyperspectral images

    Publication Year: 2010 , Page(s): 927 - 933
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1476 KB)  

    To compress hyperspectral images, a low complexity discrete cosine transform (OCT)-based distributed source coding (OSC) scheme with Gray code is proposed. Unlike most of the existing OSC schemes, which utilize transform in spatial domain, the proposed algorithm applies transform in spectral domain. Set-partitioning-based approach is applied to reorganize OCT coefficients into waveletlike tree structure and extract the sign, refinement, and significance bitplanes. The extracted refinement bits are Gray encoded. Because of the dependency along the line dimension of hyperspectral images, low density paritycheck-(LOPC)-based Slepian-Wolf coder is adopted to implement the OSC strategy. Experimental results on airborne visible/infrared imaging spectrometer (AVIRIS) dataset show that the proposed paradigm achieves up to 6 dB improvement over OSC-based coders which apply transform in spatial domain, with significantly reduced computational complexity and memory storage. View full abstract»

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  • Super-resolution image reconstruction based on three-step-training neural networks

    Publication Year: 2010 , Page(s): 934 - 940
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1603 KB)  

    A new method of super-resolution image reconstruction is proposed, which uses a three-step-training error backpropagation neural network (BPNN) to realize the super-resolution reconstruction (SRR) of satellite image. The method is based on BPNN. First, three groups learning samples with different resolutions are obtained according to image observation model, and then vector mappings are respectively used to those three group learning samples to speed up the convergence of BPNN, at last, three times consecutive training are carried on the BPNN. Training samples used in each step are of higher resolution than those used in the previous steps, so the increasing weights store a great amount of information for SRR, and network performance and generalization ability are improved greatly. Simulation and generalization tests are carried on the well-trained three-step-training NN respectively, and the reconstruction results with higher resolution images verify the effectiveness and validity of this method. View full abstract»

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  • SRV constraint based FIB design for wideband linear array

    Publication Year: 2010 , Page(s): 941 - 947
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1173 KB)  

    Frequency-invariant beamformer (FIB) design is a key issue in wideband array signal processing. To use commonly wideband linear array with tapped delay line (TDL) structure and complex weights, the FIB design is provided according to the rule of minimizing the sidelobe level of the beam pattern at the reference frequency while keeping the distortion less response constraint in the mainlobe direction at the reference frequency, the norm constraint of the weight vector and the amplitude constraint of the averaged spatial response variation (SRV). This kind of beamformer design problem can be solved with the interior-point method after being converted to the form of standard second order cone programming (SOCP). The computer simulations are presented which illustrate the effectiveness of our FIB design method for the wideband linear array with TDL structure and complex weights. View full abstract»

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  • Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

    Publication Year: 2010 , Page(s): 948 - 953
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1010 KB)  

    To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR). View full abstract»

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  • Adaptive detector design of MIMO radar with unknown covariance matrix

    Publication Year: 2010 , Page(s): 954 - 960
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (856 KB)  

    The problem of detecting signal with multiple input multiple output (MIMO) radar in correlated Gaussian clutter dominated scenario with unknown covariance matrix is dealt with. The general MIMO model, with widely separated sub-arrays and co-located antennas at each sub-array, is adopted. Firstly, the generalized likelihood ratio test (GLRT) with known covariance matrix is obtained, and then the Rao and Wald detectors are devised, which have proved that the Rao and Wald test coincide with GLRT detector. To make the detectors fully adaptive, the secondary data with signal-free will be collected to estimate the covariance. The performance of the proposed detector is analyzed, however, it is just ancillary. A thorough performance assessment by several numerical examples is also given, which has considered the sense with co-located antennas configure of transmitters and receivers array. The results show that the performance the proposed adaptive detector is better than LJ-GLRT, and the loss can be acceptable in comparison to their non-adaptive counterparts. View full abstract»

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  • Hierarchical interacting multiple model algorithm based on improved current model

    Publication Year: 2010 , Page(s): 961 - 967
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1381 KB)  

    Interacting multiple models is the hotspot in the research of maneuvering target models at present. A hierarchical idea is introduced into IMM algorithm. The method is that the whole models are organized as two levels to co-work, and each cell model is an improved “current” statistical model. In the improved model, a kind of nonlinear fuzzy membership function is presented to get over the limitation of original model, which can not track weak maneuvering target precisely. At last, simulation experiments prove the efficient of the novel algorithm compared to interacting multiple model and hierarchical interacting multiple model based original “current” statistical model in tracking precision. View full abstract»

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  • Instantaneous measurement for radar target polarization scattering matrix

    Publication Year: 2010 , Page(s): 968 - 974
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1266 KB)  

    Adopting “simultaneous transmitting, simultaneous receiving” operational scheme, instantaneous polarization radar (IPR) can measure target polarization scattering matrix (PSM) using only once target echoes in two orthogonal polarization channels. Firstly, signal model and signal process are advanced under narrowband condition. Secondly, measurement performances of two typical IPR waveforms are analyzed in detail. At last, field experiments are carried out using X-band I PR system designed by National University of Defense Technology (NUDT), China. Compared with results obtained by alternative polarization measurement scheme, following results can be obtained: the difference of relative amplitude measurement results is smaller than 2 dB and that of relative phase measurement results is smaller than 10°, verifying the validity of instantaneous polarization measurement scheme. View full abstract»

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  • Dynamic programming methodology for multi-criteria group decision-making under ordinal preferences

    Publication Year: 2010 , Page(s): 975 - 980
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (499 KB)  

    A method of minimizing rankings inconsistency is proposed for a decision-making problem with ran kings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the ran kings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences' inconsistency in multi-criteria group decision-making (MCGDM) and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result. View full abstract»

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  • Robust data envelopment analysis based MCDM with the consideration of uncertain data

    Publication Year: 2010 , Page(s): 981 - 989
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (435 KB)  

    The application of data envelopment analysis (DEA) as a multiple criteria decision making (MCDM) technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the appearance of uncertainties on input and output data of decision making unit (DMU) might make the nominal solution infeasible and lead to the efficiency scores meaningless from practical view. This paper analyzes the impact of data uncertainty on the evaluation results of DEA, and proposes several robust DEA models based on the adaptation of recently developed robust optimization approaches, which would be immune against input and output data uncertainties. The robust DEA models developed are based on input-oriented and outputoriented CCR model, respectively, when the uncertainties appear in output data and input data separately. Furthermore, the robust DEA models could deal with random symmetric uncertainty and unknown-but-bounded uncertainty, in both of which the distributions of the random data entries are permitted to be unknown. The robust DEA models are implemented in a numerical example and the efficiency scores and ran kings of these models are compared. The results indicate that the robust DEA approach could be a more reliable method for efficiency evaluation and ranking in MCDM problems. View full abstract»

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  • Linear goal programming approach to obtaining the weights of intuitionistic fuzzy ordered weighted averaging operator

    Publication Year: 2010 , Page(s): 990 - 994
    Cited by:  Papers (3)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (524 KB)  

    The multiple attribute decision making problems are studied, in which the information about attribute weights is partly known and the attribute values take the form of intuitionistic fuzzy numbers. The operational laws of intuitionistic fuzzy numbers are introduced, and the score function and accuracy function are presented to compare the intuitionistic fuzzy numbers. The intuitionistic fuzzy ordered weighted averaging (IFOWA) operator which is an extension of the well-known ordered weighted averaging (OWA) operator is investigated to aggregate the intuitionistic fuzzy information. In order to determine the weights of intuitionistic fuzzy ordered weighted averaging operator, a linear goal programming procedure is proposed for learning the weights from data. Finally, an example is illustrated to verify the effectiveness and practicability of the developed method. View full abstract»

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  • Attributes reduct and decision rules optimization based on maximal tolerance classification in incomplete information systems with fuzzy decisions

    Publication Year: 2010 , Page(s): 995 - 999
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (633 KB)  

    A new approach to knowledge acquisition in incomplete information system with fuzzy decisions is proposed. In such incomplete information system, the universe of discourse is classified by the maximal tolerance classes, and fuzzy approximations are defined based on them. Three types of relative reducts of maximal tolerance classes are then proposed, and three types of fuzzy decision rules based on the proposed attribute description are defined. The judgment theorems and approximation discernibility functions with respect to them are presented to compute the relative reduct by using Boolean reasoning techniques, from which we can derive optimal fuzzy decision rules from the systems. At last, three types of relative reducts of the system and their computing methods are given. View full abstract»

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  • New type of conjugate gradient algorithms for unconstrained optimization problems

    Publication Year: 2010 , Page(s): 1000 - 1007
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (530 KB)  

    Two new formulaes of the main parameter βk of the conjugate gradient method are presented, which respectively can be seen as the modifications of method HS and PRP. In comparison with classic conjugate gradient methods, the new methods take both available gradient and function value information. Furthermore, their modifications are proposed. These methods are shown to be global convergent under some assumptions. Numerical results are also reported. View full abstract»

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  • Human resources allocation for aircraft maintenance with predefined sequence

    Publication Year: 2010 , Page(s): 1008 - 1013
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1116 KB)  

    There are always large-scale items in the maintenances schedule of aircraft system, many of which have been fixed to be done in predefined sequences, which leads the workflow to be systematically complex and makes this kind of problem quite different from all sorts of existing job-selection modes. On the other hand, the human resources are always limited and men have different working capabilities on different items, which make the allocation operation of human resources be much roomy. However, the final total time span of maintenance is often required to be as short as possible in many practices, in order to suffer only the lowest cost of loss while the system is stopping. A new model for optimizing the allocation if aircraft maintenance human resources with the constraint of predefined sequence is presented. The genetic algorithm is employed to find the optimal solution that holds the shortest total time span of maintenance. To generate the ultimate maintenance work items and the human resource array, the sequences among all maintenance work items are considered firstly, the work item array is then generated through traversal with the constraint of maintenance sequence matrix, and the human resources are finally allocated according to the work item array with the constraint of the maintenance capability. An example is demonstrated to show that the model and algorithm behave a satisfying performance on finding the optimal solution as expected. View full abstract»

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  • DTHMM based delay modeling and prediction for networked control systems

    Publication Year: 2010 , Page(s): 1014 - 1024
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1050 KB)  

    In the forward channel of a networked control system (NCS), by defining the network states as a hidden Markov chain and quantizing the network-induced delays to a discrete sequence distributing over a finite time interval, the relation between the network states and the network-induced delays is modelled as a discrete-time hidden Markov model (DTHMM). The expectation maximization (EM) algorithm is introduced to derive the maximumlikelihood estimation (MLE) of the parameters of the DTHMM. Based on the derived DTHMM, the Viterbi algorithm is introduced to predict the controller-to-actuator (C-A) delay during the current sampling period. The simulation experiments demonstrate the effectiveness of the modelling and predicting methods proposed. View full abstract»

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  • Quantized dynamic output feedback control for networked control systems

    Publication Year: 2010 , Page(s): 1025 - 1032
    Cited by:  Papers (6)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (794 KB)  

    The problem of the quantized dynamic output feedback controller design for networked control systems is mainly discussed. By using the quantized information of the system measurement output and the control input, a novel networked control system model is described. This model includes many networkinduced features, such as multi-rate sampled-data, quantized signal, time-varying delay and packet dropout. By constructing suitable Lyapunov-Krasovskii functional, a less conservative stabilization criterion is established in terms of linear matrix inequalities. The quantized control strategy involves the updating values of the quantizer parameters μi(i = 1,2) (μi take on countable sets of values which dependent on the information of the system measurement outputs and the control inputs). Furthermore, a numerical example is given to illustrate the effectiveness of the proposed method. View full abstract»

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  • Diffserv AQM algorithm for edge and core routers

    Publication Year: 2010 , Page(s): 1033 - 1040
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1234 KB)  

    The existing active queue management (AOM) algorithm acts on subscribers and edge routers only, it does not support differentiate-serve (Diffserv) quality of service (OoS), while the existing diffserv OoS has not considered the link capacities between edge routers and connected core routers. When a core router in a two layers' network experiences congestion, the connected edge routers have no ability to adjust their access data rates. Thus, it is difficult to achieve the congestion control for the large scale network with many edge routers and core routers. To solve these problems, two difffserve AOM algorithms are proposed for the congestion control of multilayer network. One diffserv AOM algorithm implements fair link capacities of edge routers, and the other one implements unequal link capacities of edge routers, but it requires the core routers to have multi-queues buffers and Diffserv AOM to support. The proposed algorithms achieve the network congestion control by operating AOM parameters on the conditions of proposed three theorems for core and edge routers. The dynamic simulation results demonstrate the proposed control algorithms for core and edge routers to be valid. View full abstract»

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  • Filtering of long-term dependent fractal noise in fiber optic gyroscope

    Publication Year: 2010 , Page(s): 1041 - 1045
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1213 KB)  

    Stochastic noises of fiber optic gyroscope (FOG) mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filtering methodology is proposed. Firstly, fractional differencing (FD) method is introduced to transform fractal noise into fractional white noise based on the estimation of Hurst exponent for long-term dependent fractal process, which together with the existing white noise make up of a generalized white noise. Further, an improved denoising algorithm of wavelet maxima is developed to suppress the generalized white noise. Experimental results show that the basic noise terms of FOG greatly decrease, and especially the slow drift is restrained effectively. The proposed methodology provides a promising approach for filtering long-term dependent fractal noise. View full abstract»

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  • Novel adaptive Hatch filter to mitigate the effects of ionosphere and multipath on LAAS

    Publication Year: 2010 , Page(s): 1046 - 1053
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2056 KB)  

    It has been proven that carrier smoothing and differential global positioning system (DGPS) are effective to improve the accuracy of pseudorange by reducing the noise in it and eliminating almost all the common mode errors between the ground station and user. However, another issue coming with local area augmentation system (LAAS) is how to find an adaptive smoothing window width to minimize the error on account of ionosphere delay and multipath. Based on the errors analysis in carrier smoothing process, a novel algorithm is formulated to design adaptive Hatch filter whose smoothing window width flexibly varies with the characteristic of ionosphere delay and multipath in the differential carrier smoothing process. By conducting the simulation in LAAS and after compared with traditional Hatch filers, it reveals that not only the accuracy of differential correction, but also the accuracy and the robustness of positioning results are significantly improved by using the designed adaptive Hatch filter. View full abstract»

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  • New type of adaptive control for a class of distributed time-delay systems with adaptation regard to delay parameter

    Publication Year: 2010 , Page(s): 1054 - 1062
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (879 KB)  

    The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is proposed for a memory proportional and integral (PI) feedback controller with adaptation to distributed time-delay. The feedback controller with memory simultaneously contains the current state and the past distributed information of the addressed systems. The design for adaptation law to distributed delay is very concise. The controller can be derived by solving a set of linear matrix inequalities (LMls). Two numerical examples are given to illustrate the effectiveness of the design method. View full abstract»

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  • Control of static unstable airframes

    Publication Year: 2010 , Page(s): 1063 - 1071
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1409 KB)  

    The challenge and control problems of static unstable missiles are presented. The steady-state benefits of static instability are illustrated, while the corresponding control challenge is described both by the characteristic lag of airframe and the increment of necessary control usage. Control limitation led by unstable zero-pole pair is analyzed for preliminary design and evaluation. Linear control strategy is examined wherein two and three loop acceleration autopilots with different control usages are developed using an optimal control approach combined with frequency domain constraint. The weights selection and relation with system performance are detailed. Then the nonlinear backstepping recursive method is detailed to determine how well it is able to follow command and its engineering feasibility. The results show that a static unstable missile is controllable, while the actuator bandwidth is the crucial limited factor. There should be a compromise between overall performance and actuator payment. View full abstract»

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  • Adaptive integral dynamic surface control based on fully tuned radial basis function neural network

    Publication Year: 2010 , Page(s): 1072 - 1078
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1290 KB)  

    An adaptive integral dynamic surface control approach based on fully tuned radial basis function neural network (FTRBFNN) is presented for a general class of strict-feedback nonlinear systems, which may possess a wide class of uncertainties that are not linearly parameterized and do not have any prior knowledge of the bounding functions. FTRBFNN is employed to approximate the uncertainty online, and a systematic framework for adaptive controller design is given by dynamic surface control. The control algorithm has two outstanding features, namely, the neural network regulates the weights, width and center of Gaussian function simultaneously, which ensures the control system has perfect ability of restraining different unknown uncertainties and the integral term of tracking error introduced in the control law can eliminate the static error of the closed loop system effectively. As a result, high control precision can be achieved. All signals in the closed loop system can be guaranteed bounded by Lyapunov approach. Finally, simulation results demonstrate the validity of the control approach. 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