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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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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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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 unlab.led bags＇ lab.l by learning the lab.led positive training bags and negative training *** bag is made up of several unlab.led instances.A bag is lab.led 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 lab.l 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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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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Social sensing enhanced time estimation for bus service

Social sensing enhanced time estimation for bus service

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作者： Liu, Jin Li, Juan Cui, Xiaohui Niu, Xiaoguang Sun, Xiaoping Zhou, Jing State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEAs and road condition attributions PRCAs. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEAs of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. © 2015 John Wiley & Sons, Ltd.

关键词： Buses

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Structural holes study of ICML collab.rative network

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Journal of Computational Information Systems 2014年第24期10卷 10715-10722页

作者： Duan, Weiwei Qian, Fulan Shi, Lei Zhang, Yanping School of Computer Science and Technology Anhui University Hefei China Key Lab of Intelligent Computing and Signal Processing Anhui University Hefei China

Collab.ration among authors is a pervasive phenomenon currently. Mining useful information from cooperation is a significant study to unravel relationships underneath these papers and predict potential collab.rations or future popular academic topics. This paper demonstrates the change of Structural Holes in the whole network and for some individual authors from 2009 to 2012 in ICML. This paper is going to study the biggest subset in 2009, which separates into several smaller subsets with less structural holes in 2010 and 2011, while the number of structural holes in 2012 increases. The graphs of the whole networks from 2009 to 2012 drawn by Ucinet are going to demonstrate the changes of structural holes from 2009 to 2012 and expl the reason why there are more structural holes in 2012 compared to 2010 and 2011. The reason is that the ainnumber of authors in 2012 increases about 50 percent compared to 2011, which results in that authors need to find new collab.rations and leaders may become intermediaries to connect new authors and existing authors occupying structural holes. And some authors whose papers are published on ICML continuously from 2009 to 2012 are going to be analysed to indicate the changes of their position in the network. Some authors are increasingly constrained in certain groups, while some other authors become bridges connecting different groups and some other authors changes are correspond to the changes of the whole network. They are constrained in certain subset with less structural holes in 2010 and 2011 but, due to large number of authors joining in ICML, more likely to occupy more structural holes.

关键词： Data mining

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An algorithm for reading activity recognition based on electrooculogram

An algorithm for reading activity recognition based on elect...

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International Conference on Information, Communications and signal processing

作者： Rui OuYang Zhao Lv XiaoPei Wu Anhui University Hefei Anhui CN Ministry of Education Key Lab of Intelligent Computing & Signal Processing Co-Innovation Center for Information Supply & Assurance Technology Anhui University Hefei China

ISBN: (纸本)9781467372190

The research of the relationship between eye-movement and human activity has become a hot spot in the field of the human-computer interaction. In order to recognize the eye-movement patterns related to reading tasks, an algorithm based on electrooculogram(EOG) has been proposed in this paper. In the proposed approach, wavelet packet decomposition was firstly used to smooth EOG signals during reading tasks, and then, according to the predefined coding strategy, the smoothed EOG waveform is translated into a coding string to represent current reading state. Finally, Levenshtein distance is employed to measure the similarity of the template string and the output string. The experiments under the experimental paradigms of autonomy-reading and stimulus-reading and reading with rest state have been carried out. The mean accurate has reached 90%. The experimental results indicate that the proposed algorithm can effectively recognize human reading activity state.

关键词： Electrooculography Wavelet packets Encoding Algorithm design and analysis Electrodes

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Speech enhancement based on EMD and wavelet threshold in noisy environments

Speech enhancement based on EMD and wavelet threshold in noi...

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4th International Conference on Materials Science and Information Technology, MSIT 2014

作者： Chen, Zi Qin Zhang, De Xiang Yuan, Da Ling Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China The School of Electrical Engineering and Automation Anhui University Hefei 230601 China

ISBN: (纸本)9783038351733

Speech enhancement is crucial for speech recognition accuracy. How to eliminate the effect of the noise constitutes a challenging problem in speech processing. This paper presents a new technique for speech enhancement in a noisy environment based on the empirical mode decomposition (EMD) algorithm and wavelet threshold. 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 wavelet threshold of the IMF components can be used to eliminate the effect of the noise for speech enhancement. Experimental results show that the proposed speech enhancement by de-noising algorithm is possible to achieve an excellent balance between suppresses noise effectively and preserves as many target characteristics of original signal as possible. © (2014) Trans Tech Publications, Switzerland.

关键词： Empirical mode decomposition

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