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arXiv 2018年

作者： Wollstadt, Patricia Lizier, Joseph T. Vicente, Raul Finn, Conor Martinez-Zarzuela, Mario Mediano, Pedro Novelli, Leonardo Wibral, Michael MEG Unit Brain Imaging Center Goethe-University Frankfurt Fankfurt am Main Germany Centre for Complex Systems Faculty of Engineering and IT University of Sydney SydneyNSW Australia Computational Neuroscience Lab Institute of Computer Science Tartu Estonia Data61 CSIRO EppingNSW Australia Communications and Signal Theory and Telematics Engineering University of Valladolid Valladolid Spain Computational Neurodynamics Group Department of Computing Imperial College London London United Kingdom Max Planck Institute for Dynamics and Self-Organization Göttingen Germany Campus Institute for Dynamics of Biological Networks Georg-August Universität Göttingen Germany

We present IDTxl (the Information Dynamics Toolkit xl), a new open source Python toolbox for effective network inference from multivariate time series using information theory, available from GitHub (https://***/pwollstadt/IDTxl). Information theory (Cover & Thomas, 2006;MacKay, 2003;Shannon, 1948) is the mathematical theory of information and its transmission over communication channels. Information theory provides quantitative measures of the information content of a single random variable (entropy) and of the information shared between two variables (mutual information). The defined measures build on probability theory and solely depend on the probability distributions of the variables involved. As a consequence, the dependence between two variables can be quantified as the information shared between them, without the need to explicitly model a specific type of dependence. Hence, mutual information is a model-free measure of dependence, which makes it a popular choice for the analysis of systems other than communication channels. Transfer entropy (TE) (Schreiber, 2000) is an extension of mutual information that measures the directed information transfer between time series of a source and a target variable. TE has become popular in many scientific disciplines to infer dependencies and whole networks from data. Notable application domains include neuroscience (Wibral, Vicente, & Lindner, 2014) and dynamical systems analysis (Lizier, Prokopenko, & Zomaya, 2014) (see Bossomaier, Barnett, Harré, & Lizier (2016) for an introduction to TE and a comprehensive discussion of its application). In the majority of the applications, TE is used in a bivariate fashion, where information transfer is quantified between all sourcetarget pairs. In a multivariate setting, however, such a bivariate analysis may infer spurious or redundant interactions, where multiple sources provide the same information about the target. Conversely, bivariate analysis may also miss synergistic

关键词： High level languages

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Cross-modal subspace learning for fine-grained sketch-based image retrieval

arXiv

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arXiv 2017年

作者： Xu, Peng Yin, Qiyue Huang, Yongye Song, Yi-Zhe Ma, Zhanyu Wang, Liang Xiang, Tao Bastiaan Kleijn, W. Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China National Lab of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China SketchX Lab School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Communications and Signal Processing Group Victoria University of Wellington New Zealand

Sketch-based image retrieval (SBIR) is challenging due to the inherent domain-gap between sketch and photo. Compared with pixel-perfect depictions of photos, sketches are iconic renderings of the real world with highly abstract. Therefore, matching sketch and photo directly using low-level visual clues are unsufficient, since a common low-level subspace that traverses semantically across the two modalities is non-trivial to establish. Most existing SBIR studies do not directly tackle this cross-modal problem. This naturally motivates us to explore the effectiveness of cross-modal retrieval methods in SBIR, which have been applied in the image-text matching successfully. In this paper, we introduce and compare a series of state-of-the-art cross-modal subspace learning methods and benchmark them on two recently released fine-grained SBIR datasets. Through thorough examination of the experimental results, we have demonstrated that the subspace learning can effectively model the sketch-photo domain-gap. In addition we draw a few key insights to drive future research. Copyright © 2017, The Authors. All rights reserved.

关键词： Abstracting

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Glossokinetic Potentials for a Tongue-Machine Interface: How Can We Trace Tongue Movements with Electrodes?

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IEEE Systems, Man and Cybernetics Magazine 2016年第1期2卷 6-13页

作者： Nam, Yunjun Koo, Bonkon Cichocki, Andrzej Choi, Seungjin Lab. for Advanced Brain Signal Processing RIKEN Wako Saitama351-0198 Japan School of Interdisciplinary Bioscience and Bioengineering POSTECH Pohang Gyeongbuk Korea Republic of Brain Science Institutde RIKEN Wako Saitama Japan Department of Computer Science and Engineering POSTECH Pohang Gyeongbuk Korea Republic of

Glossokinetic potentials (GKPs) refer to electrical responses involving tongue movements that are measured at electrodes placed on the scalp when the tip of the tongue touches tissue inside the mouth. GKP has been considered an electroencephalography (EEG) artifact that is removed to minimize the interference with signals from a cerebral region for successful EEG analysis. In this article, we emphasize a different side of GKP where we analyze its spatial patterns to trace tongue movements developing tongue-machine interfaces. We begin with a brief overview of GKP and its spatial patterns and then describe its potential applications to man-machine interfaces. First, we describe the spatial pattern of GKP for horizontal tongue movements and explain how it can be utilized to identify the position of the tongue. We also introduce a tongue-rudder system where this technique enables smooth control of an electric wheelchair. Then we describe GKP patterns for vertical and frontal tongue movements that are closely related to speech production. Based on this pattern, we discuss its application to silent speech recognition, which allows speech communication without using a sound. © 2015 IEEE.

关键词： Electroencephalography

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A hierarchical image matting model for blood vessel segmentation in fundus images

arXiv

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arXiv 2017年

作者： Fan, Zhun Lu, Jiewei Li, Wenji Wei, Caimin Huang, Han Cai, Xinye Chen, Xinjian Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shan'tou515063 China Department of Mathematics Shantou University Shan'tou515063 China School of Software Engineering South China University of Technology Guang'zhou510006 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Jiang'su210016 China Medical Image Processing and Analysis Lab School of Electronics and Information Engineering Soochow University Su'zhou215006 China

In this paper, a hierarchical image matting model is proposed to extract blood vessels from fundus images. More specifically, a hierarchical strategy utilizing the continuity and extendibility of retinal blood vessels is integrated into the image matting model for blood vessel segmentation. Normally the matting models require the user specified trimap, which separates the input image into three regions manually: the foreground, background and unknown regions. However, since creating a user specified trimap is a tedious and time-consuming task, region features of blood vessels are used to generate the trimap automatically in this paper. The proposed model has low computational complexity and outperforms many other state-of-art supervised and unsupervised methods in terms of accuracy, which achieves a vessel segmentation accuracy of 96.0%, 95.7% and 95.1% in an average time of 10.72s, 15.74s and 50.71s on images from three publicly available fundus image datasets DRIVE, STARE, and CHASE_DB1, respectively. Copyright © 2017, The Authors. All rights reserved.

关键词： Blood vessels

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Corrigendum to “Biological Evaluation of the Effect of Galvanic Coupling Intrabody Communication on Human Skin Fibroblast Cells”

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Wireless communications and Mobile Computing 2018年第1期2018卷

作者： Shi Lin Yue-Ming Gao Juan Cai Željka Lučev Vasić Mang-I Vai Min Du Mario Cifrek Sio-Hang Pun College of Physics and Information Engineering Fuzhou University Fuzhou *** Key Lab of Medical Instrumentation & Pharmaceutical Technology of Fujian Province Fuzhou China Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatiaunizg.hr State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macau Chinaumac.mo Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau Chinaumac.mo Key Lab of Eco-Industrial Green Technology of Fujian Province Nanping China

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On the Ergodic Capacity of Multiple Antenna Cognitive Satellite Terrestrial Networks

On the Ergodic Capacity of Multiple Antenna Cognitive Satell...

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Ad-Hoc and Sensor Networks Symposium

作者： Kang An Min Lin Tao Liang Jian Ouyang Wei-Ping Zhu College of Communications Engineering PLA University of Science and Technology National Mobile Communications Research Laboratory Southeast University Nanjing Institute of Telecommunication Technology Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications Department of Electrical and Computer Engineering Concordia University

ISBN: (纸本)9781479966653

The integration of cognitive radio (CR) into satellite networks is recognized as an effective strategy to enhance the efficiency of radio spectrum. This paper investigates the ergodic capacity of a multiple antenna cognitive satellite terrestrial network, where the secondary terrestrial system can coexist with the primary satellite system as long as the interference imposed from the secondary user (SU) to the primary user (PU) is below a predefined threshold. Specifically, the Meijer-G function based analytical expression for the ergodic capacity of the secondary network is derived, which not only provides an efficient means to evaluate the system performance but also characterize the impact of various channel parameters on the network. Finally, simulation results are provided to demonstrate the validity of the theoretical analysis.

关键词： Cognitive satellite terrestrial network Multiple antenna Ergodic capacity

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Computational analysis of the structural properties of economic and financial networks

arXiv

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arXiv 2017年

作者： Emmert-Streib, Frank Musa, Aliyu Baltakys, Kestutis Kanniainen, Juho Tripathi, Shailesh Yli-Harja, Olli Jodlbauer, Herbert Dehmer, Matthias Predictive Medicine and Data Analytics Lab Department of Signal Processing Tampere University of Technology Finland Institute of Biosciences and Medical Technology Tampere Finland Industrial and Information Management Tampere University of Technology Tampere Finland Institute for Systems Biology Seattle United States Institute for Intelligent Production Faculty for Management University of Applied Sciences Upper Austria Steyr Campus Austria Department for Biomedical Computer Science and Mechatronics UMIT - The Health and Lifesciences University Hall in Tyrol Austria College of Computer and Control Engineering Nankai University Tianjin300350 China

In recent years, methods from network science are gaining rapidly interest in economics and finance. A reason for this is that in a globalized world the interconnectedness among economic and financial entities are crucial to understand and networks provide a natural framework for representing and studying such systems. In this paper, we are surveying the use of networks and network-based methods for studying economy related questions. We start with a brief overview of graph theory and basic definitions. Then we discuss descriptive network measures and network complexity measures for quantifying structural properties of economic networks. Finally, we discuss different network and tree structures as relevant for applications. Copyright © 2017, The Authors. All rights reserved.

关键词： Finance

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Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care

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Nature communications 2019年第1期10卷 588页

作者： Lena Maier-Hein Matthias Eisenmann Annika Reinke Sinan Onogur Marko Stankovic Patrick Scholz Tal Arbel Hrvoje Bogunovic Andrew P Bradley Aaron Carass Carolin Feldmann Alejandro F Frangi Peter M Full Bram van Ginneken Allan Hanbury Katrin Honauer Michal Kozubek Bennett A Landman Keno März Oskar Maier Klaus Maier-Hein Bjoern H Menze Henning Müller Peter F Neher Wiro Niessen Nasir Rajpoot Gregory C Sharp Korsuk Sirinukunwattana Stefanie Speidel Christian Stock Danail Stoyanov Abdel Aziz Taha Fons van der Sommen Ching-Wei Wang Marc-André Weber Guoyan Zheng Pierre Jannin Annette Kopp-Schneider Division of Computer Assisted Medical Interventions (CAMI) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. l.maier-hein@dkfz.de. Division of Computer Assisted Medical Interventions (CAMI) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. Centre for Intelligent Machines McGill University Montreal QC H3A0G4 Canada. Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna 1090 Vienna Austria. Science and Engineering Faculty Queensland University of Technology Brisbane QLD 4001 Australia. Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore MD 21218 USA. CISTIB - Center for Computational Imaging & Simulation Technologies in Biomedicine The University of Leeds Leeds Yorkshire LS2 9JT UK. Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center 6525 GA Nijmegen The Netherlands. Institute of Information Systems Engineering TU Wien 1040 Vienna Austria. Complexity Science Hub Vienna 1080 Vienna Austria. Heidelberg Collaboratory for Image Processing (HCI Heidelberg University 69120 Heidelberg Germany. Centre for Biomedical Image Analysis Masaryk University 60200 Brno Czech Republic. Electrical Engineering Vanderbilt University Nashville TN 37235-1679 USA. Institute of Medical Informatics Universität zu Lübeck 23562 Lübeck Germany. Division of Medical Image Computing (MIC) German Cancer Research Center (DKFZ) 69120 Heidelberg Germany. Institute for Advanced Studies Department of Informatics Technical University of Munich 80333 Munich Germany. Information System Institute HES-SO Sierre 3960 Switzerland. Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC 3015 GD Rotterdam The Netherlands. Department of Computer Science University of Warwick Coventry CV4 7AL UK. Department of Radiation Oncology Massachusetts General Hospital Boston MA

In the original version of this Article the values in the rightmost column of Table 1 were inadvertently shifted relative to the other columns. This has now been corrected in the PDF and HTML versions of the Article.

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Improving secrecy performance via device-to-device jamming in cellular networks

Improving secrecy performance via device-to-device jamming i...

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International Conference on Wireless communications and signal processing (WCSP)

作者： Jian Ouyang Min Lin Wei-Ping Zhu Kang An Lei Wang Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications Nanjing China Nanjing Institute of Telecommunication Technology Nanjing China Department of Electrical and Computer Engineering Concordia University Montreal QC Canada College of Communications Engineering PLA University of Science and Technology Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (纸本)9781509028610

In this paper, we study the secrecy performance of a cellular network, where a device-to-device (D2D) communication shares the spectral resources with a multi-antenna base station (BS). By assuming known the channel state information (CSI) of the legitimate user and using the maximal ratio transmission (MRT) at the BS, we first derive a closed-form expression of the ergodic secrecy capacity (ESC) for the wiretap channel as well as the ergodic capacity (EC) for the D2D link. Then, we present a simple yet efficient power allocation scheme to maximize the secrecy performance while satisfying the D2D transmission requirement. Finally, numerical results are given to demonstrate the merit of our study, concluding that the interference from the D2D communication can be exploited as a friendly jammer to enhance the security transmission in cellular networks.

关键词： Device-to-device communication Cellular networks Antennas Resource management Jamming Security Optimized production technology

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Area-efficient partial-clique-energy MRF pair design with ultra-low supply voltage

Area-efficient partial-clique-energy MRF pair design with ul...

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International Symposium on Circuits and Systems

作者： Yan Li Jianhao Hu Hao Lu Jie Chen National key Lab. of Communications University of Electronic Science and Technology of China China Electrical and Computer Engineering Department University of Alberta Edmonton AB Canada

ISBN: (纸本)9781479953424

As the size of CMOS devices continues to scale down, the reliability of circuits becomes one of main challenges in low supply voltage designs. Markov Random Field (MRF) circuits, a probabilistic-based approach, can achieve higher noise immunity compared to traditional designs under conditions of ultra-low supply voltage and low threshold voltage. However, the basic MRF elements have complex structures and become a stringent factor that limits MRF-based VLSI design. In this paper, we provide a partial-clique-energy MRF (PMRF) design method, trading off the noise immunity for area efficiency. We then propose an Enhanced PMRF (EPMRF)-pair for multi-level and multi-function joint PMRF designs. The main idea is to use the joint clique energy of two complementary partial clique energies to make up performance losses. The measurement results show that, the proposed EPMRF pair can operate at 0.25 V with 10-4 dB output noise power with 5.6 dB input signal-noise ratio (SNR). With the 130 nm CMOS technology, the chip of our EPMRF based carry-look-ahead adder achieves 29% area-saving and 55% energy-saving compared to existing ultra-low supply voltage fault tolerant designs.

关键词： look-ahead adder Noise immunity Markov-Random Field clique-energy

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