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Annual IEEE Northeast Workshop on Circuits and Systems (NEWCAS)

作者： Christian Vogel Matthias Hotz Shahzad Saleem Katharina Hausmair Michael Soudan FTW Telecommunications Research Center Vienna Vienna Austria Department of Electrical Engineering National University of Computer and Emerging Sciences Islamabad Pakistan Signal Processing and Speech Communication Laboratory Graz University of Technology Graz Austria

In this paper we review the progress in the design of low-complexity digital correction structures and algorithms for time-interleaved ADCs over the last five years. We devise a discrete-time model, state the design problem, and finally derive the algorithms and structures. In particular, we discuss efficient algorithms to design time-varying correction filters as well as iterative structures utilizing polynomial based filters. Finally, we give an outlook to future research questions.

关键词： Circuits and systems Complexity theory Algorithm design and analysis Calibration Time varying systems Polynomials Time frequency analysis

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Information Generation and Lagrangian Coherent Structures in Multiscroll Attractors *

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IFAC Proceedings Volumes 2012年第12期45卷 93-98页

作者： Filipe I. Fazanaro Diogo C. Soriano Ricardo Suyama Marconi K. Madrid Romis Attux José Raimundo de Oliveira Modular Robotic Systems Laboratory (LSMR) Department of Computer Engineering and Industrial Automation (DCA) School of Electrical and Computer Engineering (FEEC) UNICAMP Brazil Centro de Engenharia Modelagem e Ciências Sociais Aplicadas Universidade Federal do ABC (UFABC) Santo André Brazil LSMR Department of Energy Control and Systems (DSCE) FEEC UNICAMP Laboratory of Signal Processing for Communications (DSPCom) DCA FEEC UNICAMP

The present work aims to apply a recently alternative approach to estimate the Lyapunov exponents that is suitable for such piecewise linear model in order of characterizing - with the aid of the metric entropy - the degree of information generated by several kinds of multiscroll attractors. Another analytical path is followed with the extraction of the corresponding Lagrangian coherent structures, which allows the determination of the dynamical system separatrices and also of the folding/stretching behavior that results in chaos. Overall, the reported study can be understood as an investigation, from distinct theoretical standpoints, of key aspects regarding the dynamic behavior of systems capable of engendering multiscroll structures.

关键词： chaotic behavior fractal dimension information generation Lagrangian coherent structures Lyapunov exponents multiscroll chaotic attractors non-smooth models

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Generalized geometry-based optimal power control in wireless networks

Generalized geometry-based optimal power control in wireless...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Wei Wang Kang G. Shin Zhaoyang Zhang Wenbo Wang Tao Peng Department of Information Science and Electronic Engineering Zhejiang Provincial Key Laboratory of Information Network Technology University of Zhejiang Hangzhou China Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Wireless Signal Processing and Networking Laboratory Beijing University of Posts and Telecommunications Beijing China

Geometry-based optimal power control was proposed in [14] to transform the power-control problem to a new geometrical problem on the position relationship between a line and some points. This scheme provides a novel visual perspective and lowers the complexity of optimization. We generalize this scheme to a larger class of power-control optimization problems so as to maximize the network utility with multiple average and peak power constraints in wireless networks. To facilitate the handling of the geometrical model, we define a subset of geometrical models with specified characteristics, called a regular geometrical model, and derive the type of power-control problems eligible for the regular geometrical model. For such a type of problems, two strategies are proposed for the construction of the regular geometrical model. Utilizing geometrical properties, we propose a novel geometry-based optimization scheme for the general power-control problem. Its computational complexity is significantly lower than the conventional algorithms. We also provide a further discussion on irregular geometrical model cases. Finally, we provide two examples of deploying the proposed geometry-based power-control scheme.

关键词： Optimization Silicon Computational modeling Interference Complexity theory Power control Wireless networks

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Using simple relays to improve physical-layer security

Using simple relays to improve physical-layer security

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IEEE International Conference on Communications in China (ICCC)

作者： Gan Zheng Jiangyuan Li Kai-Kit Wong Athina P. Petropulu Björn Ottersten Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg Department of Electrical and Computer Engineering Rutgers The State University of New Jersey USA Department of Electronic and Electrical Engineering University College London London UK Signal Processing Laboratory ACCESS Linnaeus Center KTH Royal Institute of Technology Sweden

This paper studies different uses of two cooperating relays to improve the secrecy rate of a wiretap channel. These two relays are assumed to perform only simple functions: either amplify-and-forward (AF) or jamming. Complex functions such as decode-and-forward (DF) are not considered. We study three modes of cooperation: i) cooperative jamming (CJ), ii) AF-aided beamforming and iii) mixed AF-aided beamforming and CJ, all with individual relay power constraints. While i) is known in the literature, our efforts are spent on ii) and iii). In particular, for iii), we assume that the jamming signals in two communication stages are correlated, giving rise to improved performances. We also propose a heuristic approach for selecting the appropriate cooperating mode. Simulation results illustrate the performance gain of each scheme under different channel conditions and the effectiveness of the proposed mode selection method.

关键词： Relays Jamming Interference Security Protocols Noise Physical layer

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A model-based method with joint sparsity constraint for direct diffusion tensor estimation

A model-based method with joint sparsity constraint for dire...

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IEEE International Symposium on Biomedical Imaging

作者： Yanjie Zhu Yin Wu Yuanjie Zheng Ed X. Wu Leslie Ying Dong Liang Paul C. Lauterbur Research Centre for Biomedical Imaging Shenzhen Institutes of Advanced Technology Key Laboratory of Health Informatics Chinese Academy of Sciences Shenzhen China Department of Radiology University of Pennsylvania PA USA Laboratory of Biomedical Imaging and Signal Processing Department of Electrical and Electronic Engineering University of Hong Kong Pokfulam Hong Kong China Department of Electrical Engineering and Computer Science University of Wisconsin Milwaukee Milwaukee WI USA

Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The long acquisition time greatly limits the clinical application of DTI. In this paper, a novel method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images in direct estimation of the diffusion tensor from highly undersampled k-space data. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.

关键词： Tensile stress Diffusion tensor imaging Image reconstruction Joints Compressed sensing Biological system modeling

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Erratum (“A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural signals” Neural Computation, Volume 18, Number 10, pp. 2465–2494)

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Neural Computation 2012年第4期24卷 1106-1107页

作者： Iahn Cajigas Lakshminarayan Srinivasan Neuroscience Statistics Research Laboratory Department of Anesthesia and Critical Care Massachusetts General Hospital Charlestown MA 02129 U.S.A. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139 U.S.A. and Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge MA 02139 U.S.A. Neural Signal Processing Laboratory Department of Radiology David Geffen School of Medicine University of California Los Angeles CA 90095 U.S.A.

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012年 7191 LNCS卷 V-VII页

作者： Cichocki, Andrzej Theis, Fabian Yeredor, Arie Zibulevsky, Michael Helmholtz Center Munich Institute of Bioinformatics and Systems Biology Ingolstädter Landstr. 1 85764 Neuherberg Germany Riken Brain Science Institute Laboratory for Advanced Brain Signal Processing 2-1 Hirosawa Wako-shi 351-0198 Saitama Japan Tel-Aviv University School of Electrical Engineering Tel-Aviv 69978 Israel Technion - Israel Institute of Technology Department of Computer Science Haifa 32000 Israel

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An Ultra Low Power Granular Decision Making Using Cross Correlation: Minimizing signal Segments for Template Matching

An Ultra Low Power Granular Decision Making Using Cross Corr...

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IEEE/ACM International Conference on Cyber-Physical Systems (ICCPS)

作者： Hassan Ghasemzadeh Roozbeh Jafari Embedded Systems and Signal Processing Laboratory Department of Electrical Engineering University of Texas Dallas Richardson TX USA

Wearable sensor platforms have proved effective in a large variety of new application domains including wellness and healthcare, and are perfect examples of cyber physical systems. A major obstacle in realization of these systems is the amount of energy required for sensing, processing and communication, which can jeopardize small battery size and wear ability of the entire system. In this paper, we propose an ultra low power granular decision making architecture, also called screening classifier, that can be viewed as a tiered wake up circuitry. This processing model operates based on simple template matching. Ideally, the template matching is performed with low sensitivity but at very low power. Initial template matching removes signals that are obviously not of interest from the signal processing chain keeping the rest of processing modules inactive. If the signal is likely to be of interest, the sensitivity and the power of the template matching blocks are gradually increased and eventually the microcontroller is activated. We pose and solve an optimization problem to realize our screening classifier and improve the accuracy of classification by dividing a full template into smaller bins, called mini-templates, and activating optimal number of bins during each classification decision. Our experimental results on real data show that the power consumption of the system can be reduced by more than 70% using this intelligent processing architecture. The power consumption of the proposed granular decision making module is six orders of magnitude smaller than state-of-the-art low power microcontrollers.

关键词： signal processing Decision making Biomedical monitoring Microcontrollers Correlation Monitoring computer architecture

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Objective Measure of Upper Extremity Motor Impairment in Parkinson's Disease with Inertial Sensors

Objective Measure of Upper Extremity Motor Impairment in Par...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Jeffrey D. Hoffman James McNames Biomedical Signal Processing Laboratory and graduate student in the Department of Electrical and Computer Engineering at Portland State University Department of Electrical and Computer Engineering at Portland State University

ISBN: (纸本)9781424441211

Functional motor impairment caused by Parkinson's disease and other movement disorders is currently measured with rating scales such as the Unified Parkinson's Disease Rating Scale (UPDRS). These are typically comprised of a series of simple tasks that are visually scored by a trained rater. We developed a method to objectively quantify three upper extremity motor tasks directly with a wearable inertial sensor. Specifically, we used triaxial gyroscopes and adaptive filters to quantify how predictable and regular the signals were. We found that simply using the normalized mean squared error (NMSE) as a test statistic permitted us to distinguish between subjects with and without Parkinson's disease who were matched for age, height, and weight. A forward linear predictor based on the Kalman filter was able to attain areas under the curve (AUC) in receiver operator characteristic (ROC) curves in the range of 0.76 to 0.83. Further studies and development are warranted. This technology has the potential to more accurately measure the motor signs of Parkinson's disease. This may reduce statistical bias and variability of rating scales, which could lead to trials with fewer subjects, less cost, and shorter duration.

关键词： Parkinson Disease inertia sensor Rating Scales Motor Disorders Statistical Biases Kalman filters Upper Extremity adaptive filters

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A New NSCT Based Contrast Enhancement Algorithm for Amplification of Early Signs of Ischemic Stroke in Brain CT Images

A New NSCT Based Contrast Enhancement Algorithm for Amplific...

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Iranian Machine Vision and Image processing (MVIP)

作者： Mehdi Sajjadi Rassoul Amirfattahi Mohammad Reza Ahmadzadeh Digital Signal Processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

Brain CT images are extensively used in detection of Cerebrovascular Accidents (CVA). But CT scan is not really a sensitive test for diagnosis of ischemic stroke. Most of the times, early CT images barely show or even don 't show any noticeable sign of ischemia. But it is possible to put emphasis on subtle signs of ischemia by means of image contrast enhancement. Contrast enhancement using multiscale transforms is one of the most popular approaches in recent years. Nonsubsampled Contourlet Transform (NSCT) is a directional multiscale transform that is able to take geometrical structures into account. In this paper we are about to customize this transform and improve its performance in contrast enhancement of brain CT images. To this end, we propose a set of simpler and more efficient filters for Nonsubsampled Pyramid (NSP) and introduce an improved method for modification of directional subbands' coefficients.

关键词： Filter banks Finite impulse response filter Computed tomography Equations Wavelet transforms Image enhancement

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