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1. A Novel Data Aggregation of Source Node Based on TEEN Protocol in WSN | |||
WANG Yifan,WANG Chaowei,WANG Weidong | |||
Electrics, Communication and Autocontrol Technology 15 November 2016 | |||
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Abstract:With the development of wireless communication systems and microelectronics, WSNs have been widely used in various fields. But the survival time is still the main factor restricting the development of wireless sensor networks. In this paper, we focus on the problem of redundant data in the source node, in order to solve the energy consumption problem. Based on the TEEN routing protocol, a novel data aggregation of source node based on the TEEN protocol is proposed by analyzing the energy consumption of the network, and we use a Kalman filter to reduce the data forwarding of the source nodes. Simulation results show that the proposed algorithm can effectively reduce the data from the source node, save network energy and prolong the network lifetime.????? | |||
TO cite this article:WANG Yifan,WANG Chaowei,WANG Weidong. A Novel Data Aggregation of Source Node Based on TEEN Protocol in WSN[OL].[15 November 2016] http://en.paper.edu.cn/en_releasepaper/content/4709942 |
2. Design of LDPC Convolutional Codes with Improved Cycle Property | |||
ZHOU HUA,WENG SHAOHUI | |||
Electrics, Communication and Autocontrol Technology 21 December 2015 | |||
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Abstract:The cycles property of time-varying LDPC-CCs is superior to that of time-invariant LDPC-CCs. The concept of transformed LDPC-CCs, which can be considered as the time-varying version of the non-transformed one, is introduced. Based on the weight matrix of the transformed code, a family of LDPC-CCs with improved cycle properties is obtained. When the syndrome former memory is large, the enumerators for the short cycles of the designed LDPC-CCs are optimized, i.e., the number of short cycles is minimized. | |||
TO cite this article:ZHOU HUA,WENG SHAOHUI. Design of LDPC Convolutional Codes with Improved Cycle Property[OL].[21 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4672185 |
3. Reconstruction of Sparse Signals in Heterogeneous Radar Sensor Network Based on Distributed Compressive Sensing | |||
MAO Cheng-chen,ZHU Fang-Qi,LIU Huai-Yuan,LIANG Jing | |||
Electrics, Communication and Autocontrol Technology 25 November 2015 | |||
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Abstract:In this paper, we reconstruct signals in heterogeneous sensor network (HRSN) with distributed compressive sensing (DCS). Combining different types of measurement matrices and different numbers of measurements, we investigate three different scenarios in which HRSN is used to acquiring signals for the first time. In the first scenario, there are two different types of measurement matrices. One is Gaussian measurement and the other is Fourier measurement, and each sensor applies the same numbers of measurements. In the second scenario, all sensors use the same type of measurement matrices but the number of measurements are different each other. The third scenario combines different types of measurement matrix and distinct numbers of measurements. Our simulation results show that in Scenario I, when the common sparsity is considerable, the DCS scheme can reduce the number of measurements. In Scenario II, the reconstruction situation becomes better with the increase of the number of measurements. In both Scenario I and III, joint decoding that use different types of measurement matrices performs better than that of all-Gaussian measurement matrices, but it performs worse than that of all-Fourier measurement matrices. Therefore, DSC is a good compromise between reconstruction percentage and the number of measurements in HRSN. | |||
TO cite this article:MAO Cheng-chen,ZHU Fang-Qi,LIU Huai-Yuan, et al. Reconstruction of Sparse Signals in Heterogeneous Radar Sensor Network Based on Distributed Compressive Sensing[OL].[25 November 2015] http://en.paper.edu.cn/en_releasepaper/content/4665647 |
4. Hamming Code Specification Analysis Based on Binary Tree | |||
WU Qu,LV Bo,WANG Lei,BAI Jianlong | |||
Electrics, Communication and Autocontrol Technology 09 September 2014 | |||
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Abstract:The principle basis of Hamming coding and checking which can detect and correct single error is derived based on binary tree structure. Hamming tree is constructed which is embodiment of the principle. Explain linear-block hamming coding and check specifications by constructing nonlinear structural hamming tree is logical. It presents certain principle basis for study on history and application of hamming code. | |||
TO cite this article:WU Qu,LV Bo,WANG Lei, et al. Hamming Code Specification Analysis Based on Binary Tree[J]. |
5. A CCA criterion based adaptive algorithm for blind extraction of specific signal | |||
Zhang Wei-Tao | |||
Electrics, Communication and Autocontrol Technology 22 May 2014 | |||
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Abstract:In this paper, the canonical correlation approach for blind source separation is revisited. We proposed a novel criterion for source extraction, which is proved to be equivalent to the CCA criterion. Whereas it has some advantages over the standard CCA criterion in developing fast learning algorithms. By optimizing the proposed criterion, we developed two learning algorithms for the extraction of specific signals. The first algorithm is based on the steepest descent technique, and the second one is a modified Newton algorithm. The experiment results demonstrate the effectiveness of the proposed learning algorithms, and show that the modified Newton algorithm converges much faster than the other extraction method. | |||
TO cite this article:Zhang Wei-Tao. A CCA criterion based adaptive algorithm for blind extraction of specific signal[OL].[22 May 2014] http://en.paper.edu.cn/en_releasepaper/content/4597942 |
6. A Modified Ensemble Empirical Mode Decomposition based on the signal-to-noise ratio and winning number of IMFs | |||
WANG Jingtao,XU Xiaoge,MENG Xianghua | |||
Electrics, Communication and Autocontrol Technology 18 February 2014 | |||
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Abstract:In this paper a modified ensemble empirical mode decomposition (EEMD) method is presented, which is named "winning-EEMD"(W-EEMD). Two aspects of the EEMD, the amplitude of added white noise and the number of intrinsic mode functions (IMFs), are discussed in this method. The signal-to-noise ratio is used to measure the amplitude of added noise and the winning number of IMFs (which results most frequency) is used to unify the number of IMFs. By this method, the calculation speed of decomposition is improved, and the relative error between original data and sum of decompositions is reduced. In addition, the feasibility and effectiveness of this method are proved by the example of the oceanic internal solitary wave. | |||
TO cite this article:WANG Jingtao,XU Xiaoge,MENG Xianghua. A Modified Ensemble Empirical Mode Decomposition based on the signal-to-noise ratio and winning number of IMFs[OL].[18 February 2014] http://en.paper.edu.cn/en_releasepaper/content/4585195 |
7. ELM-based image steganalysis | |||
FENG Guo-Rui, ZHANG Hai-Yan | |||
Electrics, Communication and Autocontrol Technology 17 December 2013 | |||
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Abstract:In image steganalysis applications, the urgent problem is how todesign an effective classification architecture for given large-scalefeatures. In this paper we propose an approach toautomatically improve the current classification rate under the specific steganographic methods base on ELM feature selection. This approach referred asELM revisited feature selection (ELM-RFS) can tune input weights interm of minimizing mean error. This idea is derived from cross-validation learning and one-dimensional optimal search. During updating of inputweights, we seek the energy decreasing direction directly to discard the influence of leastsignificant features using the leave-one-out (LOO) selection, instead of the updated one-dimensional search at the current energy decreasing direction. The experimental resultsdemonstrate and verify that the new approach is less classification errorthan other classifier such as SVM, direct ELM-LOO learning andconventional ELM in state-of-the-art features. | |||
TO cite this article:FENG Guo-Rui, ZHANG Hai-Yan. ELM-based image steganalysis[OL].[17 December 2013] http://en.paper.edu.cn/en_releasepaper/content/4569229 |
8. Intelligent Extraction of Fine Granularity Information from Web Page | |||
Liu Han,Zhang Bin | |||
Electrics, Communication and Autocontrol Technology 20 October 2013 | |||
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Abstract:with an outburst of web information growth, web fine particle size information extraction becomes more important. However, information extraction commonly used at present has shortcoming in poor universality, complex model and rough result. This paper proposed a robust approach to extract fine granularity information via the research in web page content characteristic, structure and natural language heuristic rules. The method extracted web information in hierarchy and transformed coarse granularity web page gradually into fine granularity web page, and then identified the fine particle size information by word similarity to form structured web page attribute items. Finally, this paper conducted experiments over multiple websites to validate the proposed algorithm and give profound analysis towards experimental results. The analysis indicates that the proposed algorithm has the warrant of good applicability as well as high accuracy extraction.????? | |||
TO cite this article:Liu Han,Zhang Bin. Intelligent Extraction of Fine Granularity Information from Web Page[OL].[20 October 2013] http://en.paper.edu.cn/en_releasepaper/content/4563853 |
9. Signal Reconstruction of Non-uniform 3D configuration Distributed SAR Moving Target 3D Imaging Based on Compressed Sensing | |||
Liu Mei,Zhang Lei,Gu guanglin | |||
Electrics, Communication and Autocontrol Technology 28 September 2013 | |||
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Abstract:In this paper, a distributed SAR moving targets 3D imaging method based on compressed sensing algorithm is presented. The moving target 3D signal sparse signal model is derived, and then the moving targets 3D signal reconstruction method based basis pursuit is established. In the case of low amount of data, we realize the distributed SAR moving target high-resolution 3D imaging. Finally, the simulation results verify the correctness and validity of the proposed algorithm | |||
TO cite this article:Liu Mei,Zhang Lei,Gu guanglin. Signal Reconstruction of Non-uniform 3D configuration Distributed SAR Moving Target 3D Imaging Based on Compressed Sensing[OL].[28 September 2013] http://en.paper.edu.cn/en_releasepaper/content/4561339 |
10. A confidential target tracking algorithm in video sequences based on CS theory | |||
LIU JIA,ZHANG CHENG,WEI SUI | |||
Electrics, Communication and Autocontrol Technology 09 September 2013 | |||
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Abstract:Combined with compressive sensing theory and classical background subtraction method, this paper proposes a CS-based secrecy tracking algorithm, provided with confidential characteristic. This algorithm can track target and protect privacy synchronously, so it has the advantage of privacy protection, which other classical background subtraction algorithms doesn't have. In addition, for the introduction of CS, measurement matrix and the process of projection can be viewed as key and encryption of sensitive areas respectively, which can't be decrypted by the decoder if the key is unknown. Simulation results show that our algorithm can effectively reconstruct real image from the incomplete measurements with the right measurement matrix, and can also have the advantage of computational secure which can be more useful in some secrecy applications. | |||
TO cite this article:LIU JIA,ZHANG CHENG,WEI SUI. A confidential target tracking algorithm in video sequences based on CS theory[OL].[ 9 September 2013] http://en.paper.edu.cn/en_releasepaper/content/4559239 |
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