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Canadian Conference on electrical and computer engineering (CCECE)

作者： R. Barry W. Kinsner TR Laboratories (Telecommunications Research Laboratories) Winnipeg MAN Canada Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

A novel multifractal approach to telecommunications traffic classification is presented as an improvement over traditional traffic classifiers. The fundamental advantages of using multifractal measures include normalization and a very high compression ratio of a signature of the traffic, thus leading to more reliable and faster implementations, and the ability to add new traffic classes without redesigning the traffic classifier. The variance fractal dimension trajectory is used to provide a multifractal "signature" for each type of traffic over its duration. As a multifractal, the Renyi dimension spectrum is constructed to show the unique characteristics of each type of traffic. A probabilistic neural network is trained with the variance fractal dimension trajectory of the traffic, and has demonstrated 90.7% classification accuracy with a 585:1 compression ratio, and 90.4% classification accuracy with a 1024:1 compression ratio.

关键词： Fractals Telecommunication traffic Communication system traffic control Traffic control Neural networks Microwave integrated circuits Telecommunication network reliability Telecommunication control Local area networks Wide area networks

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A Biologically Motivated Phase-Offset to the Piecewise-Linear Model of Instantaneous Heart-Rate Interpolation

A Biologically Motivated Phase-Offset to the Piecewise-Linea...

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Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

作者： M. Potter W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg Manitoba Canada R3T 5V6

This paper formalizes the general theory of instantaneous heart-rate (IHR) interpolation from electrocardiogram RR-intervals. This paper also introduces a novel extension to the current basic piecewise-linear interpolation method which allows the discontinuity of the IHR interpolation to be offset from the R-wave. Thus an entire heart cycle can be modelled with a constant IHR. This phase-offset piecewise-linear IHR interpolation model is derivedfrom the general theory of IHR interpolation and results are demonstrated on some true recorded RR-sequences. Recursive and batch matrix forms are derived. Stable solutions can be found for any offset not equal to it radians, though the IHR calculated with a nonzero offset has a significant change to the HRV statistics. Applications of this method to the synthesis of ECG with natural heart-rate variability is also discussed.

关键词： instantaneous heart-rate IHR heart-rate vari-ability HRV electrocardiogram ECG RR-interval.

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Some advances in cognitive informatics

Some advances in cognitive informatics

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IEEE International Conference on Cognitive Informatics

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

This paper summarizes a few recent developments in cognitive informatics, with special emphasis on signal processing for autonomic computing and its metrics.

关键词： Cognitive informatics signal processing Biomedical measurements Pollution measurement Fractals Acoustic noise Biological materials Biomedical materials Cognition Humans

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Progressive transmission of images through fractal surface interpolation

Progressive transmission of images through fractal surface i...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： R. Dansereau W. Kinsner TR Laboratories (Telecommunications Research Laboratories) Winnipeg MAN Canada Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper presents a progressive image transmission technique based on fractal surface interpolation (FSI). This technique is an extension of our previous work, and relies on the extraction and reconstruction of self-affine fractal surfaces with specified Hurst exponents, H/sup */. Fractional Brownian motion (fBm) through midpoint displacement (MPD) provides the basis for generating these surfaces between interpolation points. Progressive transmission is achieved by ordering increasing levels of detail within the FSI representation. This allows for quicker recognition of the transmitted or reconstructed image within the first 5 percent of the transmission process.

关键词： Fractals Interpolation Surface reconstruction Image reconstruction Brownian motion Image coding data compression Laboratories Image communication Image recognition

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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 2005

作者： Faghfouri, A. Kinsner, W. Swatek, D. Dept. of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg Man. R3T 5V6 Canada Insulation Engineering and Testing Department Manitoba Hydro 1840 Chervier Blvd. Winnipeg Man. R3C 2P4 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 Rényi 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. © 2005 IEEE.

关键词： Lightning

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compression of aerial ortho images based on image denoising

Compression of aerial ortho images based on image denoising

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data compression Conference (DCC)

作者： A. Langi W. Kinsner TR Laboratories Telecommunications Research Laboratories Winnipeg MAN Canada Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

Abstract only given. Discusses the compression of an important class of computer images, called aerial ortho images, that result from geodetic transformation computations [Kinsner, 1994]. The computations introduce numerical noise, making the images nearly incompressible losslessly because of their high entropy. The use of classical lossy compression schemes is also not desirable because their effects on the original image are unknown. We then propose the use of image denoising coupled with lossless image compression, that preserves selected image characteristics. Two denoising schemes for a compression ratio of 2:1 are compared. The first scheme is based on a Donoho's (1992) wavelet shrinking scheme which preserves image smoothness. We study the effect of various shrinking parameter values on the compression ratio and image quality, where 35.5 dB peak signal-to-noise ratio (PSNR) is obtained for a compression ratio of 2.03:1. This approach preserves high-frequency information, so that sharp edges do not become blurred as in classical filtering methods. This is critically important, because the main feature of ortho images is in its flatness and its precision of edge position. The second scheme is based on preserving pixel predictability [Kostelich and Schreiber, 1993), leading to a variant of planar predictive coding. This approach adds, to the edge preserving capability, the limitation in pixel deviation between the original and denoised images to be within one grayscale level. As a result, two different predictive coding schemes achieve a compression ratio of 2:1 at 49.9 dB and 51.2 dB PSNR.

关键词： Image coding Image denoising PSNR Predictive coding Entropy Noise reduction Image quality Information filtering Information filters Pixel

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Multifractal characterization for classification of self-affine signals

Multifractal characterization for classification of self-aff...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： R.L. Barry W. Kinsner J. Pear T. Martin Department of Electrical and Computer Engineering Signal and Data Compression Laboratory Department of Psychology University of Manitoba Winnipeg MAN Canada Department of Psychology TRLabs (Telecommunications Research Laboratories) Winnipeg Manitoba Canada

In this paper, a novel multifractal approach to the classification of unknown self-affine signals is presented as an improvement over traditional traffic signal classifiers. The fundamental advantages of using multifractal measures include normalization and a very high compression ratio of a signature of the traffic, thereby leading to faster implementations, and the ability to add new traffic classes without redesigning the traffic classifier. The variance fractal dimension trajectory is used to provide a multifractal "signature" for each type of traffic over its duration, and the modelling of its statistical histograms provides further compression and generalization. Principal component analysis is used to reduce the dimensionality of the data, and the k-means clustering algorithm is used to determine the number of classes in the multifractal signatures. A probabilistic neural network is then trained with these signatures, and its performance on classifying unknown traffic is used to indicate the most likely number of classes in the data.

关键词： Fractals Traffic control Telecommunication traffic Communication system traffic control Telecommunication computing Neural networks Video recording Local area networks Wide area networks ISDN

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YES2 DHS: a space tether control subsystem

YES2 DHS: a space tether control subsystem

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Canadian Conference on electrical and computer engineering (CCECE)

作者： S. Dueck N. Gadhok M. Kinsner J. Kraut T. Tessier W. Kinsner Signal and Data Compression Lab Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada Department of Electrical and Computer Engineering McMaster University Hamilton ONT Canada Bristol Aerospace Limited Winnipeg MAN Canada

This paper describes the architecture and laboratory prototype implementation of the data handling subsystem (DHS) contributed by Team Canada to the Young Engineers' Satellite (YES2) project YES2 is a space-tether initiative of the European space agency uniting thirty universities in Europe, Canada, Asia, and Australia. The purpose of the DHS is to control a 35 km swinging tether for insertion of a low-mass payload into the Earth' s atmosphere from a low-orbiting spacecraft such as the International Space Station. Single event effects, absence of convective cooling, and tether length estimation are the primary design challenges. As a consequence, key software and hardware design features include radiation mitigation, power minimization, thermal mitigation, pulse detection and emphasis on discrete components. The DHS has recently undergone interface testing with teams from Spain, Italy, and Germany at the first YES2 test readiness review at ESTEC with launch scheduled on a Russian carrier for 2005.

关键词： Testing Laboratories Prototypes data handling Aerospace engineering data engineering Design engineering Satellites Educational institutions Europe

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Enhanced fractal image coding by combining IFS and VQ

Enhanced fractal image coding by combining IFS and VQ

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IEEE International Conference on Image Processing

作者： J.-L. Dugelay A. Gersho Department of Multimedia Communications Institut EURECOM France Signal Compression Laboratory Department of Electrical & Computer Engineering University of California Santa Barbara CA USA

A novel paradigm for fractal coding selectively corrects the fractal code for selected domain blocks with an image-adaptive VQ codebook. The codebook is generated from the initial uncorrected fractal code and is there... 详细信息

关键词： Fractals Image coding Image reconstruction Iterative decoding Distortion measurement computer errors Bit rate Error correction Upper bound Encoding

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Multimedia Classification via Tensor Linear Discriminant Analysis

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IEEE Transactions on Broadcasting 2024年第4期70卷 1139-1152页

作者： Chang, Shih-Yu Wu, Hsiao-Chun Yan, Kun Chih-Hao Huang, Scott Wu, Yiyan San Jose State University Department Of Applied Data Science San JoseCA95192 United States Louisiana State University School Of Electrical Engineering And Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center For Ai Applications Taoyuan32003 Taiwan Guilin University Of Electronic Technology Guangxi Key Laboratory Of Wireless Wideband Communication And Signal Processing Department Of Information And Telecommunication Guilin541004 China National Tsing Hua University Department Of Electrical Engineering Hsinchu300 Taiwan Western University Department Of Electrical And Computer Engineering LondonONN6A 3K7 Canada

Linear discriminant analysis (LDA) is a well-known feature-extraction technique for data analytic and pattern classification. As the dimensionality of multimedia data has increased in this big era, it is often to characterize data by tensors. Over the past two decades, researchers have thus explored to extend LDA to the general tensor space, especially in two common ways: LDA of tensors using tensor decomposition methods (by conversion of tensors to matrices) and LDA of tensors built upon the T-product. However, both of the aforementioned approaches have restrictions thereby. A critical problem about how to carry out LDA of arbitrary scatter tensors based on the Einstein product still remains unsolved by the existing methods. Therefore, we propose a novel tensor LDA (a.k.a. TLDA) approach, which can carry out the LDA of arbitrary-dimensional scatter-tensors without any need of tensor decomposition. Besides, for reducing the computation time, we also design a parallel paradigm to execute our proposed TLDA in this work. Numerical experiments conducted over real multimedia data demonstrate the efficacy of our proposed new TLDA in terms of classification accuracy. Moreover, the comparison of the classification accuracies, computational-complexities, and memory-complexities of our proposed novel TLDA scheme and other existing tensor-based LDA methods is made. By leveraging TLDA for high-dimensional feature extraction, segmentation, and user-item interaction data processing, future multimedia recommendation systems can facilitate more accurate, engaging, and satisfactory user experience over the Internet. © 1963-12012 IEEE.

关键词： Tensors

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