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SVM-Based Tool to Detect Patients with Multiple Sclerosis Using a Commercial EMG sensor

SVM-Based Tool to Detect Patients with Multiple Sclerosis Us...

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sensor array and multichannel signal processing workshop

作者： Konstantin Akhmadeev Aya Houssein Saïd Moussaoui Einar A. HØgestØl Ingerid Tutturen Hanne F. Harbo Steffan D. Bos-Haugen Jennifer Graves David-Axel Laplaud Pierre-Antoine Gourraud LS2N UMR 6004 Université de Nantes Nantes Frances Ecole Centrale Nantes LS2N UMR 6004 Nantes France Department of Neurology University of Oslo Oslo Norway Department of Neurology Oslo University Hospital Oslo Norway Department of Neurology University of California San Francisco San Francisco CA USA INSERM Centre de Recherche en Transplantation et Immunologie UMR 1064 Nantes France

Multiple sclerosis (MS) is a major auto-immune disease that is the leading cause of non-traumatic impairment of the central nervous system (CNS) in young adults. Successful treatment of MS patients depends on accurate tools for both the MS diagnosis and the disability progression. In current and upcoming studies the authors aim to explore the capabilities of applying a commercial electromyographic and inertial sensor (MYO Armband by Thalmic Labs Inc.), coupled with a multichannel signal processing tool, to standard neurological examination of MS progression. In this pilot study we formulate a two-class “healthy control” - “having MS” classification problem. A dataset of electromyographic signals and inertial sensor measurements from 71 individuals (31 MS patients and 40 healthy controls) was acquired during standard neurological examination routine. Temporal and spectral features of the signals were extracted in order to train and validate a classification model. Finally, a Support Vector Machine classifier was obtained giving AUROC = 0.94, 95% CI = [0.88, 0.99]. We propose a set of signal descriptors that correlate with objective components of the neurological examination. The proposed signal acquisition and processing technique, being easy to integrate into the traditional neurological exam, may have high potential for aiding in quantifying MS progression.

关键词： Electromyography Feature extraction Protocols signal processing Support vector machines Multiple sclerosis Foot

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Wireless sensing of flow-induced vibrations for pipeline integrity monitoring

Wireless sensing of flow-induced vibrations for pipeline int...

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sensor array and multichannel signal processing workshop

作者： A. Awawdeh S.T.S. Bukkapatnam S.R.T. Kumara C. Bunting R. Komanduri Electrical Engineering Oklahoma State University USA PA USA Mechanical and AeroSpace Engineering Oklahoma State University USA

Modern societies rely on a steady flow of utilities including water and gas through pipelines. Third party interventions (e.g., sabotage), sediments buildup, effects of abnormal temperatures and sustained dynamic loading adversely affect the flow patterns. They oftentimes lead to blocks, leakage and catastrophic failures in the utility grids. Round-the-clock monitoring of the vast array of pipeline network has therefore become crucial. This paper investigates the application of an ad-hoc wireless network coupled with accelerometer sensors for non-invasive continuous monitoring of flow rate and other flow patterns in large pipeline networks. The sensors rely on tracking flow-induced vibrations to directly estimate the change in the flow rate, and thus provide a means for detection and early warning of integrity loss in pipeline infrastructure.

关键词： Wireless sensor networks Pipelines Condition monitoring Vibrations Large-scale systems Aerodynamics sensor systems Accelerometers Fatigue Industrial engineering

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Linear Convergence of Iteratively Reweighted Least Squares for Nuclear Norm Minimization

Linear Convergence of Iteratively Reweighted Least Squares f...

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sensor array and multichannel signal processing workshop

作者： Christian Kümmerle Dominik Stöger Department of Computer Science University of North Carolina at Charlotte Charlotte NC USA Department of Mathematics KU Eichstätt-Ingolstadt Ingolstadt Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Low-rank matrix recovery problems are ubiquitous in many areas of science and engineering. One approach to solve these problems is Nuclear Norm Minimization, which is itself computationally challenging to solve. Iteratively Reweighted Least Squares (IRLS) uses a sequence of suitable (re-)weighted least squares problems to minimize the nuclear norm. However, while global convergence guarantees have been established for IRLS in this context, no convergence rates have been known so far. In this paper, we show that an IRLS variant named MatrixIRLS converges to the ground truth solution with a linear rate. Numerical simulations corroborate our theoretical findings.

关键词： array signal processing Conferences Minimization Numerical simulation Convergence sensor arrays

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Overdemodulation-Aided One-Bit DoA Estimation

Overdemodulation-Aided One-Bit DoA Estimation

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sensor array and multichannel signal processing workshop

作者： Saeid Sedighi Bhavani Shankar Mysore R Björn Ottersten Valeo Schalter und Sensoren GmbH Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Sensing and communication systems commonly employ quadrature demodulation for signal down-conversion to baseband, using two orthogonal sinusoidal signals–an approach well-suited for systems equipped with high-resolution Analog-to-Digital Converters (ADCs). However, the performance of this approach is compromised when constrained to one-bit resolution ADCs. Motivated by this fact, in this paper, we explore the problem of one-bit DoA estimation, where the received signal is deliberately overdemodulated using multiple offset sinusoidal signals in the coherent analog down conversion before being processed by a one-bit ADC. Through numerical analysis, we reveal that the overdemodulation technique substantially enhances the accuracy of one-bit DoA estimation.

关键词： Direction-of-arrival estimation Accuracy array signal processing Numerical analysis Conferences Estimation sensors

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Calibration of Polarimetric Antenna arrays Using Neural Networks

Calibration of Polarimetric Antenna Arrays Using Neural Netw...

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sensor array and multichannel signal processing workshop

作者： Jannik Springer Philipp Mikus Marc Oispuu Wolfgang Koch Peter Knott Fraunhofer Institute for Communication Information Processing and Ergonomics FKIE Wachtberg Germany Fraunhofer Institute for High Frequency Physics and Radar Techniques FHR Wachtberg Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper addresses the problem of calibration for antenna arrays with multi-port polarimetric elements. Model-based array signal processing techniques require an accurate model of the complex array response and model errors can, for example, cause significant systematic direction finding errors. Modeling the response of polarimetric antenna arrays can be particularly challenging due to cross-polarization and mutual coupling effects in the multi-port antenna elements. This work proposes a new calibration technique for polarimetric antenna arrays using neural networks that learn any mismatches between the modeled and the actual array response. The technique is evaluated based on the measured response of a five-element dual-polarized antenna array and outperforms conventional calibration techniques like mutual coupling calibration or local polynomial approximation. Its performance is studied exemplarily for the direction finding problem.

关键词： Antenna measurements Training Direction-of-arrival estimation Systematics array signal processing Artificial neural networks Parallel processing

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Direct Position Determination of Locally Scattered Sources Using Generalized array Manifold Model

Direct Position Determination of Locally Scattered Sources U...

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sensor array and multichannel signal processing workshop

作者： Devan Palur Palanivelu Marc Oispuu Wolfgang Koch Thomas Dallmann Fraunhofer Institute for Communication Information Processing and Ergonomics FKIE Wachtberg Germany Radio Technologies for Automated and Connected Vehicles Research Group Technische Univcrsität Ilmenau Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Source localization from raw array data by repa-rameterizing the array steering vector by the source position is a fundamental principle of direct position determination (DPD). In this paper, we propose a DPD method to estimate the position of locally scattered sources using an unsynchronized array sensor network. Here, we use the well-known generalized array manifold (GAM) model which approximates the steering vector using its first-order gradient in order to characterize the local scattering effect. The proposed method is compared with the conventional two-stage bearings-only localization (BOL) approach. Simulation results reveal that the proposed DPD position estimates asymptotically attain the derived Cramér-Rae Bound (CRB) for high SNR values and an improved localization accuracy is achieved by exploiting the local scattering parameters in the localization.

关键词： Location awareness Manifolds Accuracy Systematics array signal processing Scattering Vectors

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DOA Estimation of Quasi-Stationary signals in Uniform Linear arrays With Mutual Coupling

DOA Estimation of Quasi-Stationary Signals in Uniform Linear...

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sensor array and multichannel signal processing workshop

作者： Ping Chu Jinfeng Zhang Bin Liao College of Electronics & Information Engineering Shenzhen University Shenzhen China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals (QSS) in uniform linear arrays (ULAs) with unknown mutual coupling is considered. By taking advantage of the quasi-stationarity of signals and the special structure of mutual coupling matrix (MCM) of ULAs, a computational efficient algorithm is devised to determine the DOAs. Different from the existing approaches for DOA estimation with unknown mutual coupling, the proposed method can simultaneously enjoy various superiorities including: 1) it is computationally efficient without the need of spectral search, 2) it can resolve more sources, and 3) it is robust against unknown noise. Simulations are conducted to demonstrate the effectiveness and superiority of the proposed DOA estimator.

关键词： Mutual coupling Direction-of-arrival estimation array signal processing Simulation Conferences Estimation signal processing algorithms

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Sample complexity trade-offs for synthetic aperture based high-resolution estimation and detection

Sample complexity trade-offs for synthetic aperture based hi...

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sensor array and multichannel signal processing workshop

作者： Heng Qiao Pulak Sarangi Yazeed Alnumay Piya Pal Department of Electrical and Computer Engineering University of California San Diego

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper critically examines the potential performance benefits offered by motion of sparse arrays for direction- of-arrival (DOA) estimation. The motivation behind utilizing array motion is to increase the number of consecutive difference lags. However, creating a synthetic array also requires more temporal measurements compared to the static (non-synthetic) array. For the first time, we rigorously analyze the trade-off between the required number of temporal samples and the length of the difference co-array to understand when synthetic arrays offer distinct advantages. As a concrete result, we show that if the ratio of the number of consecutive lags of the difference coarray of sparse arrays with and without motion is above a universal threshold, the synthetic array outperforms its non-synthetic counterpart and has a smaller estimation error. Our claims are demonstrated both theoretically and through numerical experiments 1 .

关键词： Estimation error Direction-of-arrival estimation array signal processing Atmospheric measurements Conferences Apertures Particle measurements

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Beam Pattern Synthesis for Conformal array with Sidelobe and Polarization Control: A Penalized Inequality Approach

Beam Pattern Synthesis for Conformal Array with Sidelobe and...

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sensor array and multichannel signal processing workshop

作者： Tianyu Cao Wenqiang Pu Pengyu Zhang Zhi-Quan Luo Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China The China Electronics Technology Group Corporation China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Conformal array is attractive due to its flexibility to attach to different shape of surface. However, beam pattern synthesis for conformal array to control power side lobes and different polarization components for two dimensional angle space is a challenge, especially the degree of freedom is limited. In this work, we propose a robust beam pattern synthesis formulation for conformal array based on constrained convex optimization. By penalizing the maximum gain of cross-polarization component levels, power side lobes and different polarization components are controlled in a manner that the number of constraints is no longer limited by the array DoF. The proposed formulation is a convex second-order cone programming, a computationally efficient algorithm based on the alternating directions of multipliers method is designed to solve it. Simulations demonstrate the effectiveness of the proposed formulation to synthesize a desired pattern with robustness.

关键词： array signal processing Shape signal processing algorithms Programming Parallel processing Brain modeling Robustness

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sensor Management with Uncertain Performance Characteristics

Sensor Management with Uncertain Performance Characteristics

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sensor array and multichannel signal processing workshop

作者： M.P. Kolba L.M. Collins Electrical and Computer Engineering Department Duke University Durham NC USA

Previous work has presented an information-theoretic sensor management framework for the detection of static targets. This framework is based on the expected discrimination gain maximization technique of Kastella. The sensor manager searches for N targets within a grid of cells using M sensors, which may be thought of as a reconfigurable sensor array. sensor probabilities of detection and false alarm are used in the mathematical structure of the sensor manager, and these probabilities have previously been assumed to be certain. Realistic problems, however, will inevitably involve uncertainty. This paper introduces uncertain sensor P d and P f values into the mathematical framework and allows for their incorporation into the sequential structure of the sensor manager. The performance of the presented sensor management technique is then compared to direct search, where the sensors sweep through the grid in a predefined sampling pattern. The sensor manager is found to be superior to direct search when the uncertainty present in the problem is properly modeled. When uncertainty is present but not modeled, the performance of the sensor manager is severely degraded. This result indicates that uncertainty modeling will be important and necessary for the successful application of the presented sensor manager to real-world problems. Additional simulations examine the robustness of the sensor manager to errors in the assumed densities for P d and P f , and the performance of the sensor manager is found to remain strong even when the assumed P d and P f densities differ from the true densities

关键词： sensor phenomena and characterization sensor arrays Uncertainty Multimodal sensors Engineering management Humans Landmine detection Gain measurement Sampling methods Degradation

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