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International conference on data Science and Business Analytics (ICDSBA)

作者： Dai Yu Wang Xuan Long Wenjia Yu Peng Ma Junyu Zhixing College of Hubei University Wuhan China

Moving target monitoring is widely used in many fields such as industrial control, military, and security. Traditional moving target monitoring generally uses infrared, ultra-sonic and other technologies, which have the disadvantages of complex implementation technology, high hardware cost and high environmental requirements. this paper proposes a low-cost, easy-to-deploy, and small-scale environment with little environmental impact by collecting GPS monitoring signals of multi-target speed and location and signal transmission and processing methods based on ZigBee wireless ad hoc network. signal acquisition and real-time data storage, transmission and processing methods have high application value and promotion significance.

关键词： Industrial control Zigbee Memory Real-time systems Hardware Trajectory Security

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Robust 1-Bit Compressed Sensing via Hinge Loss Minimization 13

Robust 1-Bit Compressed Sensing via Hinge Loss Minimization

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13th International conference on Sampling theory and Applications (SampTA)

作者： Genzel, Martin Stollenwerk, Alexander Tech Univ Berlin Dept Math Berlin Germany Rhein Westfal TH Aachen Chair Math Anal C Aachen Germany

ISBN: (纸本)9781728137414

We study the problem of estimating a structured high-dimensional signal x(0) subset of R-n from noisy 1-bit Gaussian measurements. Our recovery approach is based on a simple convex program which uses the hinge loss function as data fidelity term. While such a risk minimization strategy is typically applied in classification tasks, its capacity to estimate a specific signal vector is largely unexplored. In contrast to other popular loss functions considered in signal estimation, which are at least locally strongly convex, the hinge loss is just piecewise linear, so that its "curvature energy" is concentrated in a single point. It is therefore somewhat unexpected that we can still prove very similar types of recovery guarantees for the hinge loss estimator, even in the presence of strong noise. More specifically, our error bounds show that stable and robust reconstruction of x(0) can be achieved with the optimal approximation rate O(m(-1/2)) in terms of the number of measurements Tn. Moreover, we permit a wide class of structural assumptions on the ground truth signal, in the sense that x(0) can belong to an arbitrary bounded convex set K subset of R-n. For the proofs of our main results we invoke an adapted version of Mendelson's small ball method that allows us to establish a quadratic lower bound on the error of the first order Taylor approximation of the empirical hinge loss function.

关键词： Convex optimization

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LEARNING LAPLACIAN MATRIX FROM BANDLIMITED GRAPH signalS 44

LEARNING LAPLACIAN MATRIX FROM BANDLIMITED GRAPH SIGNALS

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44th IEEE International conference on Acoustics, Speech and signal processing (ICASSP)

作者： Le Bars, Batiste Humbert, Pierre Oudre, Laurent Kalogeratos, Argyris Univ Paris Saclay ENS Cachan CNRS CMLA F-94235 Cachan France Univ Paris 13 L2TI F-93430 Villetaneuse France Sigfox R&D F-31670 Labege France

ISBN: (纸本)9781479981311

In this paper, we present a method for learning an underlying graph topology using observed graph signals as training data. the novelty of our method lies on the combination of two assumptions that are imposed as constraints to the graph learning process: i) the standard assumption used in the literature that signals are smooth with respect to graph structure (i.e. small signal variation at adjacent nodes), with ii) the additional assumption that signals are bandlimited, which implies sparsity in the signals' representation in the spectral domain. the latter assumption affects the inference of the whole eigenvalue decomposition of the Laplacian matrix and leads to a challenging new optimization problem. the conducted experimental evaluation shows that the proposed algorithm to solve this problem outperforms a reference state-of-the-art method that is based only on the smoothness assumption, when compared in the graph learning task on synthetic and real graph signals.

关键词： Graph learning graph signal processing signal representation bandlimited signals sparse coding

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A Chinese Remainder theorem Based Perfect Secret Sharing Scheme with Enhanced Secret Range Values Using Tensor Based Operations 13

A Chinese Remainder Theorem Based Perfect Secret Sharing Sch...

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13th International conference on signal processing and Communication Systems, ICSPCS 2019

作者： Milanezi, Jayme Da Costa, Joao Paulo C. L. Maranhão, João Paulo A. De Sousa, Rafael T. Del Galdo, Giovanni Department of Electrical Engineering University of Brasilia Brasília-DF Brazil Institute for Information Technology Ilmenau University of Technology Ilmenau Germany Brazilian Electricity Regulatory Agency ANEEL Brasília-DF Brazil Fraunhofer Institute for Integrated Circuits IIS Ilmenau Germany

ISBN: (纸本)9781728121949

Protecting sensitive information is an increasingly difficult task due to the advances in hardware. Brute force attacks (BFA) have been successful in accessing protected data. As BFA is a trial and error process, and a natural solution against it consists of enhancing the range of possible secret values. One of the most used cryptographic techniques to protect sensitive data is the Secret Sharing Scheme (SSS), by means of which one can protect the secret by mathematically and individually distributing it into shares over n participants. Only when a minimal quantity of t participants combine their shares the secret is revealed to all of them. Among the several applications of the Chinese Remainder theorem (CRT), it is also used as a SSS. Although the state-of-the-art Asmuth-Bloom's SSS is perfect in terms of secrecy, the candidate values for the secret are quite small, therefore enhancing the probability of a successful BFA, as less values are to be tested by the attacker. In this paper, we propose a new and perfect CRT based SSS based on sparse matrices. the secret is an integer that, by means of the Lehmer Code, has a bijective relationship with the permutations of the values in a vector constructed with the shares. In the proposed CRT based SSS, the secret can assume a set of values that largely outperforms the range of values obtained with the Asmuth-Bloom's SSS. Furthermore, it is mathematically proven to be potentially unlimited. Considering for instance a set of 6 co-prime numbers under 100, the gain in secret range compared with the Asmuth-Bloom's SSS per bits used is 10103 higher. © 2019 IEEE.

关键词： Sensitive data

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An ECG Morphological Analysis Algorithm for Hybrid Patient Monitoring 6th

An ECG Morphological Analysis Algorithm for Hybrid Patient M...

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6th International conference on Advancements of Medicine and Health Care through Technology (MediTech)

作者： Raza, A. Farago, Paul Cirlugea, M. Hintea, S. Tech Univ Cluj Napoca Fac Elect Telecommun & Informat Technol Bases Elect Dept George Baritiu 26-28 Cluj Napoca 400027 Romania

ISBN: (纸本)9789811362071;9789811362064

Screening and diagnosis in ubiquitous healthcare environments is performed by the medical staff in the presence of a variety of medical data originating from continuous in vivo patient monitoring. this assumes the correlation of data, such as vital signs, biopotentials, activity tracking, bio-markers, etc., in the context of hybrid clinical monitoring. the hybrid patient monitoring setup envisioned in this work targets the simultaneous assessment of body fluids via electro-optical means and of electrophysiological data, i.e. electrocardiogram, via biopotential monitoring. Accordingly, the aim of this paper is to propose an electrocardiogram morphological analysis algorithm applicable in the framework of the envisioned hybrid monitoring setup. Electrocardiogram morphological analysis is performed in time domain in two stages. the R, S and Q waves are first identified via comparison to a threshold value. then, the P and T waves are identified via cross-correlation to a reference signal. the novelty of this work is that cross-correlation is performed after the QRS complex was eliminated from the electrocardiogram. Expectedly, this leads to improved results in wave identification and to a reduction of false detections. Matlab simulation results validate the proposed procedure.

关键词： Biomedical equipment Biomedical monitoring Biomedical signal processing signal processing algorithms

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An Infrared small Target Detection Method Based on Block Compressed Sensing 13th

An Infrared Small Target Detection Method Based on Block Com...

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13th International conference on Intelligent Information Hiding and Multimedia signal processing (IIH-MSP)

作者： Yang, Jingli Cui, Zheng Jiang, Shouda Harbin Inst Technol Dept Automat Test & Control Xidazhistr 92 Harbin 150080 Heilongjiang Peoples R China

ISBN: (纸本)9783319638560;9783319638553

Aiming at improving the real-time performance of infrared weapon systems, a method based on block compressed sensing is proposed to detect infrared small target, which is also easy to be implemented with hardware. the proposed method can detect and locate small infrared targets by classifying compressed results of blocks. In addition, in order to solve the low detection accuracy caused by using uniform block, the proposed method uses overlapping blocks to reduce the maximum distance between the center of the test sample block and that of the target. Experiments show that the proposed method can effectively improve the detection accuracy of infrared small targets.

关键词： Compressed sensing Infrared target detection Overlapping blocks

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NEURAL NETWORK MAXIMIZING ORDINALLY SUPERVISED MULTI-VIEW CANONICAL CORRELATION FOR DETERIORATION LEVEL ESTIMATION 26

NEURAL NETWORK MAXIMIZING ORDINALLY SUPERVISED MULTI-VIEW CA...

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26th IEEE International conference on Image processing (ICIP)

作者： Maeda, Keisuke Takahashi, Sho Ogawa, Takahiro Haseyama, Miki Hokkaido Univ Fac Informat Sci & Technol Kita Ku N-14W-9 Sapporo Hokkaido 0600814 Japan Hokkaido Univ Fac Engn Kita Ku N-13W-8 Sapporo Hokkaido 0608628 Japan

ISBN: (纸本)9781538662496

this paper presents a neural network maximizing ordinally supervised multi-view canonical correlation for deterioration level estimation. the contributions of this paper are twofold. First, in order to calculate features representing deterioration levels on transmission towers, which is one of the infrastructures, a novel neural network handling multi-modal features is constructed from a small amount of training data. Specifically, in our method, effective transformation to features with high discriminant ability without using many hidden layers is realized by setting projection matrices maximizing correlation between multiple features into hidden layer's weights. Second, since there exists ordinal scale in deterioration levels, the proposed method newly derives ordinally supervised multi-view canonical correlation analysis (OsMVCCA). OsMVCCA enables estimation of the effective projection considering not only label information but also their ordinal scales. Experimental results show that the proposed method realizes accurate deterioration level estimation.

关键词： Neural network ordinal scale canonical correlation deterioration level estimation

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Foreword

ICETE 2020 - Proceedings of the 17th International Joint Con...

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ICETE 2020 - Proceedings of the 17th International Joint conference on e-Business and Telecommunications 2020年 XI-XII页

作者： Callegari, Christian Ng, Soon Xin Sarigiannidis, Panagiotis Battiato, Sebastiano de León, Ángel Serrano Sánchez Ksentini, Adlen Lorenz, Pascal Obaidat, Mohammad Ben-Othman, Jalel Italy University of Southampton United Kingdom University of Western Macedonia Greece University of Catania Italy Universidad Rey Juan Carlos Spain Eurecom France University of Haute Alsace France College of Computing and Informatics University of Sharjah United Arab Emirates University of Jordan Jordan and University of Science and Technology Beijing China University of Paris 13 France

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Radar reflectivity spatial profile of 3D surrogate targets and real vehicles

Radar reflectivity spatial profile of 3D surrogate targets a...

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European conference on Antennas and Propagation, EuCAP

作者： Henrik Toss Kristian Karlsson RISE Safety & Transport/Electronics Research Institutes of Sweden/RISE Borås Sweden

In this paper a method to find a radar reflectivity spatial profile for comparing 3D surrogate targets with real vehicles is proposed. Utilizing this method, the spatial profile can be acquired using only high-level data from an automotive grade radar. For data within a small angular window at arbitrary aspect angle relative to the target, the proposed method back-projects Radar Cross Section (RCS) detections, to build up a spatial profile. this profile can then be used to evaluate multiple scattering centers on targets, which are important during test of autonomous vehicles and active safety functions. the method is used on measured data from 3D surrogate targets as well as real vehicles, which are presented in the paper.

关键词： Radar cross-sections Radar antennas Radar detection Automobiles Radar imaging Europe

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New Doppler processing for the Detection of small and Slowly-Moving targets in Highly Ambiguous Radar Context 26

New Doppler Processing for the Detection of Small and Slowly...

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European signal processing conference (EUSIPCO)

作者： Aouchiche, Linda Ferro-Famil, Laurent Adnet, Claude Univ Rennes 1 Rennes France Thales Air Syst Limours France

ISBN: (纸本)9789082797015

this paper presents a novel Doppler processing scheme for pulse Doppler radars operating in at intermediate Pulse Repetition Frequency (PRF) and suffering from range and Doppler ambiguities. One of the main drawbacks of the classical Doppler processing approach concerns the suppression of small and slowly-moving targets when rejecting ground clutter returns. In order to address this problem a two-step Doppler method is proposed in this paper. the first step uses a new iterative algorithm that resolves ambiguities and detects fast (exo-clutter) targets. the detection of slow (endo-clutter) targets is then performed by an adaptive detection scheme that uses a new covariance matrix estimation technique. Pulse trains with different characteristics are then associated for enhanced detection performance.

关键词： Doppler effect Clutter Covariance matrices Training data signal resolution Estimation Doppler radar

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