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IEEE International Conference on Cognitive Informatics

作者： W. Kinsner Institute of Industrial Mathematical Sciences Telecommunications Research Laboratory Canada Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

Numerous attempts are being made to develop machines that could act not only autonomously, but also in an increasingly intelligent and cognitive manner. Such cognitive machines ought to be aware of their environments which include not only other machines, but also human beings. Such machines ought to understand the meaning of information in more human-like ways by grounding knowledge in the physical world and in the machines' own goals. The motivation for developing such machines range from self-evidenced practical reasons such as the expense of computer maintenance, to wearable computing in health care, and gaining a better understanding of the cognitive capabilities of the human brain. To achieve such an ambitious goal requires solutions to many problems, ranging from human perception, attention, concept creation, cognition, consciousness, executive processes guided by emotions and value, and symbiotic conversational human-machine interactions. This paper discusses some of the challenges emerging from this new design paradigm, including systemic problems, design issues, teaching the subjects to undergraduate students in electrical and computer engineering programs, research related to design.

关键词： Intelligent systems Humans Machine intelligence Wearable computers Grounding Medical services Cognition Symbiosis Man machine systems Education

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Comparison of entropy-based characterization of lightning strike maps using planar and spherical coordinates

Comparison of entropy-based characterization of lightning st...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： A. Faghfouri W. Kinsner D. Swatek Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada Insulation Engineering and Testing Department Manitoba Hydro Winnipeg MAN Canada

In this paper, effects of including the curvature of the Earth in the characterization of the lightning strike maps (LSMs) are studied. Lightning strikes can adversely affect the power generation and distribution systems, and behaviour prediction of such LSMs is of interest for protection and planning in the power industry. Characterization is one of the important stages of the behaviour prediction. We have shown that multifractal measures such as the Renyi fractal dimension spectrum (RS) are appropriate for characterization of such LSMs which are self-affine. The computation of the RS is based on estimating the probability density function (pdf) of the lightning strikes distribution. Since the LSMs range from very large to low densities over a large geographical area such as Manitoba, computing this pdf in planar coordinates is subject to a nonlinear error due to the curvature of the Earth. Thus, modelling and calculating the maps in spherical coordinates yields a better estimation of the pdf. The data of the LSMs have been collected by the Canadian Lightning Detection Network (CLDN) during the year 2002. The LSMs of Manitoba are characterized through regular (using planar coordinates) and modified (using spherical coordinates) RS techniques. The results indicate that regular RS technique alters the characteristics of the feature space, especially in latitudinal direction, and causes sparser features in the feature space, while using the modified RS technique alleviates all these problems, and provides a more accurate characterization which is necessary for a reliable classification of the maps

关键词： Lightning Earth Fractals Power generation planning Power system protection Power system planning Power industry Distributed computing Probability density function Yield estimation

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A comparative study to select an image deconvolution method

A comparative study to select an image deconvolution method

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International Multi-Conference on Systems, signals and Devices

作者： Saadi, S. Kouzou, A. Guessoum, A. Bettayeb, M. Department of Electronics University Ziane Achour of Djelfa Algeria Department of Electronics Signal and Image Processing Laboratory USDB Blida Algeria Department of Electrical and Computer Engineering University of Sharjah United Arab Emirates

ISBN: (纸本)9781424475346

Image deconvolution is an important subject in image processing. It is an ill-posed inverse problem, so regularization techniques are used to solve this problem by adding constraints to the objective function. Various popular algorithms have been developed to solve such problem. This paper studies various approaches to the nonlinear degraded images restoration problem which are useful in many images enhancement applications. Swarm intelligence is applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method which is often used. In this work, we attempt to reconstruct or recover corrupted images that have been degraded during acquisition;using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition (TSVD) method is also considered for image deconvolution in this paper. A comparison between these methods made on examples is included. ©2010 IEEE.

关键词： Image enhancement

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Bacterial foraging algorithm for neutron radiography image quality improvement

Bacterial foraging algorithm for neutron radiography image q...

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International Multi-Conference on Systems, signals and Devices

ISBN: (纸本)9781424475346

We want to implement a new optimal approach for image restoration problem, which is useful for neutron radiography images enhancement to assist the physician interpreter on his evaluation. Our approach is based on using swarm intelligence optimization algorithms to solve a least squares minimization ill-posed problem, using Bacterial Foraging Optimization (BFO) Algorithm. To get smoothed images in presence of noise, a Laplacian constraint is introduced for regularization purpose. ©2010 IEEE.

关键词： Image reconstruction

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Block Sparse Bayesian Learning for Bursty Impulsive Noise Detection in Broadband PLC 2

Block Sparse Bayesian Learning for Bursty Impulsive Noise De...

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2nd International Conference on Imaging, signal Processing and Communication, ICISPC 2018

作者： Mariyam, Prita Dewi Liu, Jing Juwono, Filbert H. Gunawan, Dadang Universitas Indonesia Department of Electrical Engineering Depok West Java16424 Indonesia National Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Curtin University Malaysia Department of Electrical and Computer Engineering Miri Sarawak98009 Malaysia

ISBN: (纸本)9781538669822

Broadband power-line communications (PLC) is considered as an enabling technology for the Internet-of-Things (IoT) systems. However, PLC faces some transmission issues as a power line was not designed to transmit communication data. Impulsive noise is one of the major issues in broadband PLC systems. In practice, impulsive noise may occur in bursts. The performance of the PLC systems degrades significantly under bursty impulsive noise environment. We propose to use a compressive sensing algorithm to detect and mitigate the bursty impulsive noise. In this paper, block sparse Bayesian learning (BSBL) algorithms are used to detect and estimate the bursty impulsive noise. The estimated impulsive noise is then subtracted from the contaminated signal. BSBL has relatively better performance than other block compressive sensing algorithms. We examine the performance of two types of BSBL algorithms, i.e. BSBL-bound optimization (BSBL-BO) and BSBL-expectation-maximization (BSBL-EM) under various bursty impulsive noise conditions. The results show that both algorithms have comparable performance in terms of bit error rate (BER). However, BSBL-EM gives better minimum square error (MSE) but much slower in the CPU processing time than BSBL-BO. © 2018 IEEE.

关键词： Impulse noise

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Multifractal characterization and fuzzy classification of lightning strike maps

Multifractal characterization and fuzzy classification of li...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

This paper investigates optimal classification of lightning strike maps (LSMs), using regular and fuzzy K-means classifiers. It also describes a novel approach for measurements of the physical LSMs. Lightning strikes are physical phenomena, which have adverse effects on power transmission. Modelling and classification of the LSMs can lead to prediction of their time-space behaviour, and enhance the protection of the existing and new power systems and transmission lines. Prediction requires the classification of the simulated results and physical data, and comparing them together using characterization. Since the LSMs are highly nonlinear, nonstationary, and stochastic, ordinary models and analyses are incapable of simulating and characterizing these phenomena. Since self-affinity of such maps is an indication of multifractality, percolation models and complexity measures such as the Renyi fractal dimension spectrum (RS) and Mandelbrot singularity spectrum (MS) are utilized. The data of the LSMs have been obtained through the Canadian Lightning Detection Network (CLDN) for Manitoba in the year 2002. The data have been characterized by both the RS and MS. Features have been extracted using the RS. Classification employed the regular and fuzzy K-means methods. For each classification method, 50 tests have been utilized, and classification performance for 2 to 15 classes has been investigated through Davis-Bouldin criterion. The fuzzy K-means classifier identified 6 optimal classes with a confidence level of 0.78, while the regular K-means algorithm could not distinguish the classes.

关键词： Fractals Lightning Power system modeling Power system simulation Predictive models Power system protection Transmission line measurements Power transmission Power system analysis computing Power system measurements

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Predistorter design employing parallel piecewise linear structure and inverse coordinate mapping for broadband communications

Predistorter design employing parallel piecewise linear stru...

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14th European signal Processing Conference, EUSIPCO 2006

作者： Cheong, Mei Yen Werner, Stefan Laakso, Timo I. Cousseau, Juan Figueroa, Jose L. Signal Processing Laboratory Center of Excellence Helsinki University of Technology Finland CONICET Department of Electrical Engineering and Computer Science Universidad Nacional Del sur Bahía Blanca Argentina

This paper proposes a low-complexity predistorter (PD) for compensation of both the AM/AM and the AM/PM conversions with memory. The nonlinear power amplifier (PA) is modeled as a Wiener type nonlinearity. The quasi-static nonlinearities are modeled using a class of piecewise linear (PWL) functions. The PWL function facilitates an efficient PD identification algorithm. The proposed algorithm involves a novel inverse coordinate mapping (ICM) method that maps the nonlinear characteristics of the PA to that of the PD, and parameter estimations that do not require matrix inversion. The indirect learning architecture is used to provide an on-line compensation of thememory effect of the PA. Simulation results show that the PD that compensates also the AM/PM distortion performs significantly better than one that considers only the AM/AM nonlinearity. The proposed PD is also shown to outperform the orthogonal polynomial PD in both adjacent channel interference suppression and inband distortion compensation.

关键词： Power amplifiers

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Tracking articulator movements using orientation measurements

Tracking articulator movements using orientation measurement...

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2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012

作者： Ji, An Johnson, Michael T. Berry, Jeffrey Marquette University Department of Electrical and Computer Engineering Speech and Signal Processing Laboratory P. O. Box 1881 Milwaukee WI 53201-1881 United States

ISBN: (纸本)9781467301718

This paper introduces a new method to track articulator movements, specifically jaw position and angle, using 5 degree of freedom (5 DOF) orientation data. The approach uses a quaternion rotation method to accomplish this jaw tracking during speech using a single senor on the mandibular incisor. Data were collected using the NDI Wave Speech Research System for one pilot subject with various speech tasks. The degree of jaw rotation from the proposed approach is compared with traditional geometric calculation. Results show that the quaternion based method is able to describe jaw angle trajectory and gives more accurate and smooth estimation of jaw kinematics. © 2012 IEEE.

关键词： Degrees of freedom (mechanics)

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Mathematical model of human forearm based muscle fiber tissues’ anisotropic characteristics

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Open Biotechnology Journal 2016年 10卷 234-238页

作者： Qin, Yu-Ping Zhang, Shuang Liu, Yi-He The Engineering and Technical College Chengdu University of Technology Leshan614000 China The College of Computer Science Neijiang Normal University Neijiang641000 China The State Key Laboratory of Analog and Mixed-signal VLSI University of Macau 999078 China The Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau 999078 China

On the basis of human muscle fiber tissues’ characteristics,it is first proposed to establish the analytical model of galvanic coupling intra-body communication channel. In this model,the parallel and the transverse electrical characteristics of muscular tissue are fully considered,and the model accurately presents the transmission mechanism of galvanic coupling intra-body communication signals in the channel. © Qin et al.

关键词： Analytical models

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Maximum likelihood parameter estimation for non-Gaussian prior signal models

Maximum likelihood parameter estimation for non-Gaussian pri...

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The 1994 1st IEEE International Conference on Image Processing

作者： Schultz, R.R. Stevenson, R.L. Lumsdaine, A. Laboratory for Image and Signal Analysis Department of Electrical Engineering University of Notre Dame Notre DameIN46556 United States Department of Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States

For signals containing discontinuities, the usual assumptions of Gauss-Markov distributed signal sources do not hold. To preserve edges, non-Gaussian prior models have been developed for use in Bayesian restoration. These models are generally dependent upon two parameters, one controlling the size of reconstructed discontinuities, and the other controlling data smoothing. The authors propose a maximum likelihood technique for automatically estimating these parameters, resulting in the optimization of an expression dependent upon the prior model partition function. An exact expression is derived for the 1D signal model partition function, while an approximation is proposed for the 2D image model partition function. Parameters estimated from degraded signals result in high quality restorations. © 1994 IEEE.

关键词： Restoration

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