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International Conference on Information, Communications and signal processing

作者： Bangyan Zhou Xiaopei Wu Zhao Lv Lei Zhang Chao Zhang Ministry of Education Key Laboratory of Intelligent Computing & Signal Processing Co-Innovation Center for Information Supply & Assurance Technology Anhui University Hefei China

Considering the limitation of hardware requirement and power dissipation in wearable brain-computer interface (BCI), the electroencephalogram (EEG) data compression implemented by independent component analysis (ICA) combined with compressed sensing (CS) is proposed in this paper. A simple and effective ICA spatial filtering method is used to obtain motor related independent components (MRICs). Furthermore, CS algorithm is introduced to compress MRICs, which have advantage of frequency sparse. So the proposed scheme can make few MRICs compressed transmission instead of the multi-channel EEG data transmission. Based on the measured motor imagery EEG data, the proposed EEG compression scheme is compared with the traditional CS compression scheme. The experimental results show that, the two system schemes have the similar classification accuracy. However, in the proposed compression scheme, the amount of transmission data can be reduced by 75%.

关键词： Electroencephalography Biomedical monitoring Image reconstruction Image coding signal processing algorithms Electrodes Dictionaries

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Speech intelligibility enhancement using convolutive non-negative matrix factorization with noise prior

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous Engineering 2014年第7期9卷 73-86页

作者： Zhou, Jian Fang, Xianyong Tao, Liang Zhao, Li Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University 230601 Hefei China Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Southeast University 210096 Nanjing China

We propose a convolutive non-negative matrix factorization method to improve the intelligibility of speech signal in the context of adverse noise environment. The noise bases are prior learned with Non-negative Matrix Factorization (NMF) algorithm. A modified convolutive NMF with sparse constraint is then derived to extract speech bases from noisy speech. The divergence function is selected as an objective function to get a multiplicative update of speech base and its corresponding weight. The weights of prior learned noise bases are also updated in the update rule. Listening experiments are conducted to assess the intelligibility performance of speech synthesized using the proposed algorithm. Experimental results indicate that the proposed method is very effective to improve the intelligibility of the noisy speech in various noise contexts and it outperforms conventional algorithms. © 2014 SERSC.

关键词： Non-negative matrix factorization

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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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A novel high-capacity reversible data-hiding scheme using two steganographic images

A novel high-capacity reversible data-hiding scheme using tw...

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： You-Jing Lu Wan-Li Lyu School of Computer Science and Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

This paper proposes a novel reversible data-hiding scheme utilizing two steganographic images. The proposed method is able to hide more secret messages than other messages by studying the characters of embedded messages. We transformed the form of the secret message byte from 8 binary bits to 7-base digits, which was departed to 3-digit planes to allow for hiding more secret messages through use of an extensional key matrix M*. The horizontal and vertical coordinate of the key matrix M* ranges are from 0 to 255. Therefore, we use the pixel pairs in a cover image to help hide secret message bytes in the method proposed. In key matrix M*, a point can be located by a horizontal coordinate and a vertical coordinate, which are the exact paired pixels. After embedding data by using the coordinates in the key matrix and then obtaining two stego images, we can recover the cover image after extracting the embedded data. Experiments show that the method proposed can hide more pixels in an image and recover the image accurately with only a tiny decrease in image quality.

关键词： Image quality Visualization Histograms Mathematical model Data mining Matrix converters Computer science

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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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An improved precoding of Approximative Matrix Inverse Computations based on norm minimization algorithm in massive MIMO system

An improved precoding of Approximative Matrix Inverse Comput...

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IEEE International Conference on Progress in Informatics and computing (PIC)

作者： Hongliu Tu Yanjun Hu Yaohua Xu Fengrong Li Key laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Key Laboratory of Wireless Sensor Network & Communication Chinese Academy of Sciences Shanghai China

In massive multiple-input multiple-output (MIMO) system, scaling up the antennas of base station (BS) has a clear benefit on sum rate and energy efficiency, but the signal processing complexity can be very high and many algorithms cannot be implemented in practice for high hardware cost. Approximative Matrix Inverse Computations (AMIC) algorithm is a kind of low-complexity precoding for large multiuser MIMO systems, but the Bite Error Rate (BER) performance is shown to be not better than the classical MMSE precoding. To improve the BER performance of AMIC algorithm, in this paper, we use norm minimization algorithm to change the coefficient of the precoding matrix to improve the BER performance of AMIC algorithm. It can verify that the proposed algorithm can achieve better BER performance than the AMIC algorithm by using only a limited number of Neumann series iterations, and keep lower complexity. The proposed scheme is a compromise solution between complexity and BER performance.

关键词： Approximation algorithms Antennas Bit error rate Precoding signal to noise ratio

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Improved Anti-Occlusion Target Tracking Algorithm Based on Compressive Particle Filtering

Improved Anti-Occlusion Target Tracking Algorithm Based on C...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Yaohua Xu Xiaoli Jiang Fengrong Li Key laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Key Laboratory of Wireless Sensor Network & Communication Chinese Academy of Sciences Shanghai China

ISBN: (纸本)9781467395885

In order to resolves the problem of occlusion in process of target tracking, an improved anti-occlusion tracking algorithm was proposed in this paper based on compressive particle filtering (CPF). Compressive sensing theory was introduced into particle filter (PF) framework to ensure the instantaneity of tracking. We apply the histogram with spatial information and sub-part matching ideas in the compressive particle filtering algorithm to enhance the robustness of tracking when the target was blocked by barriers. In this approach, we adopt different strategies to tracking target when the target was occluded or not. When the target was occluded, tracking it by compressive particle filtering algorithm based on sub-part matching and updating the target templates to fits the change of target appearance, otherwise, tracking it by the general compressive particle filtering algorithm. This approach bring about better robustness and tracking speed compared with the particle filtering algorithm and compressive tracking algorithm.

关键词： Target tracking Filtering Histograms Color signal processing algorithms Compressed sensing Robustness

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An improved entity similarity measurement method

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Telkomnika (Telecommunication computing Electronics and Control) 2014年第4期12卷 1017-1022页

作者： Lv, Gang Zheng, Cheng Chen, Sheng-Bing Key of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui China Key Laboratory of Network and Intelligent Information Processing Hefei University Hefei Anhui China

To facilitate the integration of learning resources categorized under different ontology representations, the techniques of ontology mapping can be applied. Though many algorithms and systems have been proposed for ontology mapping, they do not have an automatic weighting strategy on class features to automate the ontology mapping process. A novel method of computing the feature weights is proposed. By feature semantic analysis, the different entities similarity calculation model and weight calculation model were defined. The results show that it makes the ontology mapping process more automatic while retaining satisfying accuracy. Improve ontology mapping effectiveness.

关键词： Semantics

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An Improved Precoding of Approximative Matrix Inverse Computations Based on Norm Minimization Algorithm in Massive MIMO System

An Improved Precoding of Approximative Matrix Inverse Comput...

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2015 IEEE International Conference on Progress in Informatics and computing(PIC 2015)

作者： Hongliu Tu Yanjun Hu Yaohua Xu Fengrong Li Key laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences

In massive multiple-input multiple-output（MIMO） system, scaling up the antennas of base station（BS） has a clear benefit on sum rate and energy efficiency, but the signal processing complexity can be very high and many algorithms cannot be implemented in practice for high hardware cost. Approximati ve Matrix Inverse Computations（AMIC） algorithm is a kind of lowcomplexity precoding for large multiuser MIMO systems, but the Bite Error Rate（BER） performance is shown to be not better than the classical MMSE precoding. To improve the BER performance of AMIC algorithm, in this paper, we use norm minimization algorithm to change the coefficient of the precoding matrix to improve the BER performance of AMIC algorithm. It can verify that the proposed algorithm can achieve better BER performance than the AMIC algorithm by using only a limited number of Neumann series iterations, and keep lower complexity. The proposed scheme is a compromise solution between complexity and BER performance.

关键词： Massive MIMO linear precoding algorithm approximative matrix inverse norm minimization

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On the encoding complexity of systematic polar codes

On the encoding complexity of systematic polar codes

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IEEE International SOC Conference

作者： Liping Li Wenyi Zhang Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education of China Anhui University China Chinese Academy of Sciences and Department of Electronic Engineering and Information Sciences University of Science and Technology of China

Systematic polar codes are proposed by Arikan and are shown to have better BER performance than non-systematic polar codes. From a recursive decomposition of the generator matrix of polar codes, Arikan showed that the encoding complexity of systematic polar codes is also O(N log N) where N is the code block length. But the recursive process involves some additional calculations in transforming the problem instances back and forth. In this paper, by using the sparsity property of the generator matrix, we propose an encoding process which has the same complexity as non-systematic polar codes in the presence of an additional memory array. Without the additional memory elements, the number of additions of the proposed encoding process increases compared with non-systematic polar codes. We also provide an analysis to quantify this additional increase of the complexity.

关键词： Encoding Systematics Complexity theory Decoding Generators Bit error rate Electronic mail

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