We present a new approach that automatically captures the semantic hierarchies in HTML tables, and semi-automatically integrates HTML tables belonging to a domain. It first automatically captures the attribute-value p...
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A novel estimator for integer frequency offset estimation of OFDM systems is derived, which is based on the maximum likelihood (ML) technique and exploits the differential information between two consecutive blocks of...
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ISBN:
(纸本)0780382463
A novel estimator for integer frequency offset estimation of OFDM systems is derived, which is based on the maximum likelihood (ML) technique and exploits the differential information between two consecutive blocks of OFDM data symbols in the frequency domain. The reason why the ML estimator has better performance than the conventional method is analyzed. How to select the differential sequence is also studied. By computer simulations, the performance of the ML estimator is compared with that of the conventional method for the additive white Gaussian noise (AWGN) channel and the multipath fading channel. The simulation results are in good agreement with the analytical study.
Presented herein is an efficient simulation technique enabling systematic investigation of the soft programming over-erased flash EEPROM cells. The simulation provides a method by which to find the optimal soft progra...
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This paper presents a recurrent neural network-based approach for modal parameters identification of structure-unknown systems. The proposed approach involves two steps. The first step is to build a recurrent neural n...
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ISBN:
(纸本)0780384032
This paper presents a recurrent neural network-based approach for modal parameters identification of structure-unknown systems. The proposed approach involves two steps. The first step is to build a recurrent neural network to map the complex nonlinear relation between the excitations and responses of the structure-unknown system by off-line learning. The second step is to propose a procedure to determine the modal parameters of the system from the trained neural networks. The dynamic characteristics of the structure are directly evaluated from the weighting matrices of the trained recurrent neural network. Furthermore, an illustrative example demonstrates the feasibility of using the proposed method to identify modal parameters of structure-unknown systems. The method proposed can be used to research on fault diagnosis of engineer structure.
A noncoherent reduced state differential sequence detection (RSDSD) for continuous phase modulation (CPM) is proposed in this paper. This method makes use of the reduced state trellis based on reduced state sequence d...
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ISBN:
(纸本)0780385233
A noncoherent reduced state differential sequence detection (RSDSD) for continuous phase modulation (CPM) is proposed in this paper. This method makes use of the reduced state trellis based on reduced state sequence detection (RSSD) and performs one-symbol differential Viterbi detection. The minimum Euclidean distance of the reduced state trellis is analyzed for full response CPM and partial response CPM. Bit error rates of RSSD and RSDSD are simulated for octal 2RC signal with h=1/8 in the AWGN channel and comparisons are made between the different RSSD schemes and between coherent RSSD and noncoherent RSDSD with Doppler frequency shifts. Although our proposed scheme is degraded by 2 dB at 10/sup -3/ bit error rate as compared with coherent detection, it is more appropriate and robust when the carrier recovery is difficult.
The accuracy of concrete strength inspection has a great influence on the safety evaluation of the building. In order to increase the accuracy, Fuzzy Neural Network (FNN) was built up to evaluate concrete strength. It...
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The accuracy of concrete strength inspection has a great influence on the safety evaluation of the building. In order to increase the accuracy, Fuzzy Neural Network (FNN) was built up to evaluate concrete strength. It takes full advantage of the characteristics of the common concrete testing methods: drill and rebound, and the abilities of FNN including automatic learning, generation and fuzzy logic inference. The experiment shows that the max relative error of the predicted results is 1.12%, which is satisfied with the requirements of the engineering. The method efficiently maps the complex non-linear relationship between the drill values and the rebound values, and provides a efficient way for the concrete strength inspection and evaluation.
Attack simulation plays a key role in testing Intrusion Detection System (IDS). From the viewpoint of attack testing, an attack simulation platform is put forward for testing IDS based on virtual machine technology. F...
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Attack simulation plays a key role in testing Intrusion Detection System (IDS). From the viewpoint of attack testing, an attack simulation platform is put forward for testing IDS based on virtual machine technology. First of all, the testing aims and contents of attack simulation are proposed. Then, the design and implementation of the attack simulation platform are presented in detail. Under the platform, that the authors build, three key issues in realization of the platform: the choice of testing datum, the classification of attack technology, and the attack testing zones and their compartmentalization are discussed in detail. Finally, the test results are given.
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