检索结果-内蒙古大学图书馆

Diffusion tensor based curvature-driven difiusion model for digital inpainting

Journal of Computational Information Systems 2015年第1期11卷 185-194页

作者： Qu, Lei Huang, Linsheng Wei, Sui Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

In this paper, we formulate the digital inpainting as a curvature-driven anisotropic concentration difiusing process. The difiusion strength along the gradient directions is defined as a function of curvature, so that the "Connectivity Principle" can be satisfied. Difierent to the classic Curvature-Driven Difiusion (CDD) model, the difiusion along the edge directions can be easily integrated into the difiusion equation in our model by using difiusion tensor. As result, more exibility in designing the local difiusion behavior is allowed, and the CDD model can be generalized as a special case. We show that our model can boost inpainting speed 3fi6 times and at the same time has similar inpainting quality compared to the widely used CDD model. Experimental results on synthetic and real images have verified the stability and eficiency of our model. ©, 2014, Journal of Computational Information Systems. All right reserved.

关键词： Tensors

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Hierarchical Covering Algorithm

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Tsinghua Science and Technology 2014年第1期19卷 76-81页

作者： Jie Chen Shu Zhao Yanping Zhang Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University

The concept of deep learning has been applied to many domains, but the definition of a suitable problem depth has not been sufficiently explored. In this study, we propose a new Hierarchical Covering Algorithm （HCA） method to determine the levels of a hierarchical structure based on the Covering Algorithm （CA）. The CA constructs neural networks based on samples＇ own characteristics, and can effectively handle multi-category classification and large-scale data. Further, we abstract characters based on the CA to automatically embody the feature of a deep structure. We apply CA to construct hidden nodes at the lower level, and define a fuzzy equivalence relation R on upper spaces to form a hierarchical architecture based on fuzzy quotient space theory. The covering tree naturally becomes from R. HCA experiments performed on MNIST dataset show that the covering tree embodies the deep architecture of the problem, and the effects of a deep structure are shown to be better than having a single level.

关键词： deep architecture hierarchy fuzzy equivalence relation covering tree MNIST dataset

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Speech Endpoint Detection Based on EMD and Higher Order Statistics in Noisy Environments

Speech Endpoint Detection Based on EMD and Higher Order Stat...

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2015 5th International Conference on Information Engineering for Mechanics and Materials(ICIMM 2015)

作者： Dexiang Zhang Jiaxing Li Zihong Chen Key Lab.of Intelligent Computing and Signal Processing Anhui University The School of Electrical Engineering and Automation of Anhui University

Accurate endpoint detection is crucial for speech recognition accuracy. This paper presents a new technique for speech endpoint detection in a noisy environment based on the empirical mode decomposition(EMD) algorithm and higher order statistics. With the EMD, the noise speech signals can be decomposed into a sum of the band-limited function called intrinsic mode functions(IMFs), which is a zero-mean AM-FM component. Then higher order statistics of the IMF components can be used to extract the desired feature for endpoint detection. In order to show the effectiveness of the proposed method, we present examples showing that the new measure is more effective than traditional measures. The experimental results show that the performance of the proposed algorithm is noticeable in the real speech signal tests with different SNR.

关键词： Endpoint Detection EMD Higher Order Statistics Noisy Environments

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Fusion of Polarization Image Using Bidimensional Empirical Mode Decomposition

Fusion of Polarization Image Using Bidimensional Empirical M...

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International Conference on Computer Science and Mechanical Automation

作者： Dexiang Zhang Zihong Chen Jiaxing Li Jingjing Zhang Key Lab. of Intelligent Computing and Signal Processing Anhui University The School of Electrical Engineering and Automation Anhui University

ISBN: (纸本)9781467391672

Empirical mode decomposition (EMD) provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Bidimensional empirical mode decomposition (BEMD) techniques decompose an image into several bidimensional intrinsic mode functions (BIMFs) and a bidimensional residue (BR). Firstly, several polarization images can be decomposed into several BIMFs with multi-scales using BEMD. For the BIMF coefficients, the teager energy-based method is used. For the each BIMF coefficients, the area-based teager energy larger value of information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused image. Experimental results show that the proposed algorithm gives more satisfactory results than the traditional image fusion algorithms in preserving the edges and texture information.

关键词： Bidimensional empirical mode decomposition Image decomposition Polarization image Image fusion

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A distributed high-rate and low-detection complexity cooperative relay transmission scheme

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Journal of Information and Computational Science 2014年第18期11卷 6591-6599页

作者： Xu, Lei Jiang, Ran Zhang, Gongquan Zou, Mingquan Li, Xiaohui Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

Since the existing full-rate cooperative transmission schemes have a serious defect in low Bit Error Rate (BER) performance while the existing high-rate cooperative transmission schemes have a serious defect in low spectral efficiency, a distributed high-rate cooperative relay transmission scheme based on full-rate cooperative communication model is proposed in this paper, in which Cyclic Delay Diversity (CDD) technology and Linear Constellation Precoding (LCP) technology are employed. Moreover, the proposed scheme addresses the issue of obtaining maximum spatial and multipath diversity with low decoding complexity and high transmission reliability. The BER performance of the proposed scheme is contrasted to that of the full-rate transmission scheme where better performance is achieved, and is improved when the number of the multipath or the relay nodes increases.

关键词： Bit error rate

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A mixed structure of full-rate and low-detection complexity cooperative relay transmission scheme

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Journal of Computational Information Systems 2014年第21期10卷 9339-9349页

作者： Jiang, Ran Meng, Fanzhi Li, Xiaohui Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

Since the single-antenna relay cooperative communication systems have a serious defect in reliability of data transmission, while the MIMO communication systems have difficulty in design and decoding, we propose a mixed structure of full-rate and low-detection complexity cooperative relay transmission scheme based on full-rate relay cooperative transmission model, which combines the advantages of cyclic delay diversity (CDD) technology and linear constellation precoding (LCP) technology. This scheme can excavation diversity gain by using single antenna terminal and multiple antenna simultaneously, moreover, the decoding complexity is low. The bit error rate (BER) performance is improved with the number of the antenna or the multipath or the relay nodes increases.

关键词： Cooperative communication

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A logarithmic backoff algorithm based on dynamic contention window adjustment for IEEE 802.11 DCF

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Journal of Computational Information Systems 2014年第17期10卷 7609-7617页

作者： Xu, Lei Wang, Li Xun, Huili H., Zhang X., Li Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

IEEE 802.11 is a protocol standard widely used in wireless local area network (WLAN). For the distributed coordination function (DCF) of IEEE 802.11 MAC layer, the binary exponential backoff (BEB) algorithm has the defect of poor access fairness. To address this issue, the design criteria of backoff algorithm is generalized from the analysis of the key performance parameters of DCF, and then a logarithmic backoff (LB) algorithm based on dynamic contention window (CW) adjustment is proposed. The algorithm dynamically adjusts the initial value of CW and the backoff size of the CW by using the logarithmic function that takes the number of network competing nodes as the variable. Simulation results show that compared with the BEB algorithm, the LB algorithm can effectively improve the fairness performance and the throughput performance, and also reduce network delay.

关键词： IEEE Standards

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Multiple-Instance Learning with Instance Selection via Constructive Covering Algorithm

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Tsinghua Science and Technology 2014年第3期19卷 285-292页

作者： Yanping Zhang Heng Zhang Huazhen Wei Jie Tang Shu Zhao the Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University the Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University1Hefei 230601 China the Department of Computer Science and Technology Tsinghua University

Multiple-Instance Learning （MIL） is used to predict the unlabeled bags＇ label by learning the labeled positive training bags and negative training *** bag is made up of several unlabeled instances.A bag is labeled positive if at least one of its instances is positive,otherwise *** multiple-instance learning methods with instance selection ignore the representative degree of the selected *** example,if an instance has many similar instances with the same label around it,the instance should be more representative than *** on this idea,in this paper,a multiple-instance learning with instance selection via constructive covering algorithm （MilCa） is *** MilCa,we firstly use maximal Hausdorff to select some initial positive instances from positive bags,then use a Constructive Covering Algorithm （CCA） to restructure the structure of the original instances of negative *** an inverse testing process is employed to exclude the false positive instances from positive bags and to select the high representative degree instances ordered by the number of covered instances from training ***,a similarity measure function is used to convert the training bag into a single sample and CCA is again used to classification for the converted *** results on synthetic data and standard benchmark datasets demonstrate that MilCa can decrease the number of the selected instances and it is competitive with the state-of-the-art MIL algorithms.

关键词： multiple-instance learning instance selection constructive covering algorithm maximal Hausdorff

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A full-rate cooperative relay transmission scheme with randomized cyclic delay diversity

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Journal of Computational Information Systems 2014年第1期10卷 275-284页

作者： Xu, Lei Bao, Menglin Jiang, Ran Zhang, Hongwei Li, Xiaohui Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

Randomized cyclic delay diversity (RCDD) is an effective means to capture both the space diversity and the frequency diversity with low complexity detection over frequency-selective fading channels. Since many existing full-rate cooperative relay transmission schemes have the disadvantages of low spectrum efficiency and high complexity detection, a practical and low complexity detection full-rate distributed cooperative relay transmission scheme is proposed in this paper by taking advantages of the randomized cyclic delay diversity method and the linear constellation precoding (LCP) technology. The bit error rate (BER) performance of the proposed scheme is superior to that of the system with fixed cyclic delay diversity (FCDD) when the number of subcarriers is sufficiently large. Moreover, the system diversity gain improves with the multipath number of the frequency-selective fading channel and the relay number increases. Copyright © 2014 Binary Information Press.

关键词： Cooperative communication

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Decision-making strategies for multi-objective community detection in complex networks

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 472卷 621-628页

作者： Zhang, Yu Zhang, Xingyi Tang, Jin Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230039 China

ISBN: (纸本)9783662450482

Multi-objective optimization algorithms have demonstrated their effectiveness and efficiency in detecting community structure in complex networks, by which a set of trade-off partitions of networks are obtained instead of a single partition. The large number of partitions lead to a challenging problem for decision makers: how to obtain an ideal partition from the set of trade-off partitions of networks. In this paper, we present two decision-making strategies for obtaining the ideal partition, one is based on the knee points and the other is based on the majority voting. Experimental results on random networks and real-world networks illustrate that the presented two strategies are very competitive for obtaining an ideal partition of networks. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Complex networks

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