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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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Electrical detection of single particle in cylindrical solid-state nanopores

Electrical detection of single particle in cylindrical solid...

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IEEE Conference on Electron Devices and Solid-State Circuits

作者： Yu Zhang Jun Luo Yansong Liu Minquan Li Chao Zhao Chengjun Huang Key Laboratory of Intelligent Computing and Signal Processing Anhui University China Key Laboratory of Microelectronics Device and Integrated Technology Institute of Microelectronics of Chinese Academy of Science Beijing China

This paper presented a new technique for electrical detection of single nanoparticle in a cylindrical solid-state nanopore by measuring the blockage ionic current change. Both numerical and analytical models were developed to simulate and optimize the electrical responses of the device when a single particle was passing through the nanopore. The effects of different nanopore geometries on nanoparticle detection performance were discussed, which could provide guidelines for the device fabrications and nanoparticle detection applications.

关键词： Conferences Electron devices Solid state circuits

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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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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 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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Discovery of ovarian cancer candidate genes using protein interaction information 11th

Discovery of ovarian cancer candidate genes using protein in...

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11th International Conference on intelligent computing, ICIC 2015

作者： Zhang, Di Wang, Qingbao Zhu, RongRong Li, Hai-Tao Zheng, Chun-Hou Xia, Junfeng Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Institute of Health Sciences School of Computer Science and Technology Anhui University Hefei Anhui230039 China Clinical Laboratory Center The First Affiliated Hospital Anhui University of Traditional Chinese Medicine Hefei Anhui230012 China College of Electrical Engineering and Automation Anhui University Hefei Anhui230601 China

ISBN: (纸本)9783319221854

Ovarian cancer (OVC) is one of the deadliest cancers in women. At present, effective clinical therapy for OVC is still limited. We adopted a computational method to identify OVC candidate genes based on subnetwork extraction algorithm in the protein interaction network. Of the final identified five genes, MSH3 and PIK3R3 genes have been reported to be implicated in OVC tumorigenesis, indicating that the method is effective, whereas the other three genes (MAPK8IP1, PICK1, and IQGAP3) might have potential roles in OVC development. The results provided a novel insight into identifying the OVC-related genes and exploring new methods for OVC therapy. © Springer International Publishing Switzerland 2015.

关键词： Proteins

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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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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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Calculating Nonlocal Optical Properties of Metallic Nanowires with FDTD Method

Calculating Nonlocal Optical Properties of Metallic Nanowire...

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Asia-Pacific Microwave Conference

作者： Xiang Li Ming Fang Jie Xu Zhixiang Huang Tailong Xu Xianliang Wu Key Laboratory of Intelligent Computing and Signal Processing Anhui University

ISBN: (纸本)9781479987689

We present a FDTD method which can be used to calculate the optical properties of nanostructures with nonlocal effect. The effect can be described by a spatially nonlocal dielectric function with a Drude plus two Lorentz terms model. We compared the optical properties of isolated nanowires with different radii. According to the extinction spectra, we can determine in which length scale the nonlocal effects become remarkable and should be taken into consideration in real applications. At the same time, we verify the conclusions by the transmission of nanostructures. Our method and related results can be used as a tool and reference in the design of realistic sub-wavelength devices.

关键词： Decision support systems Finite difference methods Dielectrics Nanowires

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