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检索条件"机构=Signal and Data Compression Laboratory"

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Netlist partitioning for FPGA-based run-time reconfiguration

Netlist partitioning for FPGA-based run-time reconfiguration

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： S. Dueck W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper demonstrates the feasibility of using automated netlist partitioning to improve the performance of a single FPGA run-time reconfigurable system. Run-time reconfiguration (RTR), an important model for computing, can outperform other computing solutions for some applications and exhibit high architectural flexibility. The performance of RTR is heavily influenced by circuit partitioning. While partitioning procedures to enhance RTR have been previously explored, their nature remains poorly understood. A partitioning system has, therefore, been designed and implemented in software to interface functional circuits to an industry standard graph partitioning heuristic and to study its performance. Experimental results demonstrate that a 103 gate, low-power DCT implementation with 105 nets may be bipartitioned with an interpartition bandwidth of 3 nets.

关键词： Runtime Field programmable gate arrays High performance computing Computer applications Application specific integrated circuits Logic programming data compression Laboratories Flexible printed circuits Discrete cosine transforms

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Characterizing behaviour of birth/death processes using fractal measures

Characterizing behaviour of birth/death processes using frac...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： J. Greenberg W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

The goal of this work was to determine if fractal dimensions would be useful in attempting to characterize and extract emergent behaviour from cellular automata. More specifically, we sought to determine if entropy-based fractal dimensions might prove more useful in extracting behavioural information than morphological dimensions, such as the Hausdorff dimension. This hypothesis was confirmed over several experiments by calculating the gyration dimension, Hausdorff dimension, and by finding Shannon's entropy of the automata's supporting environment during each system iteration.

关键词： Fractals Automata Entropy Lattices Topology data mining Shape Probability Genetics Cloning

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Modelling multifractal object boundaries using iterated function system

Modelling multifractal object boundaries using iterated func...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： S. Siddiqui A. El-Boustani W. Kinsner Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

This paper addresses the problem of approximation of arbitrary object boundaries that result from image segmentation. We present a new technique to reconstruct the self-similar boundaries with any fractal or multifractal dimension, using the iterated function system (IFS). The boundaries are assumed to be rough (non-smooth) but crisp (one-pixel wide) and are fractal or multifractal in nature. We show that such boundaries can be regarded as an attractor of a linear IFS having the same multifractal spectrum as the boundaries. We also discuss the hidden variable IFS in order to reconstruct multifractal boundary curvatures, while preserving the original multifractal spectrum of the boundary. Experimental results show that such arbitrary boundaries can be reconstructed more accurately using the IFS as compared to other standard techniques like the midpoint displacement algorithm.

关键词： Fractals Image segmentation Image coding Image reconstruction Video compression Shape Curve fitting data compression Laboratories MPEG 7 Standard

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Local and global analysis of multifractal singularity spectrum through wavelets

Local and global analysis of multifractal singularity spectr...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

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

This paper presents the implementation aspects pertinent to the computation of the multifractal singularity spectrum through wavelets, and the methods of overcoming them. Multifractals are mixtures of monofractals, and monofractals are self-affine objects that hold power law relationships over several scales. Such multifractals can be detected and measured through a singularity spectrum. Many natural and artificial phenomena such as turbulence, diffusion limited aggregates, and electrical discharges exhibit multifractality. Since these phenomena are highly nonlinear and nonstationary, regular analyses such as Fourier decomposition cannot characterize them effectively. In order to characterize, compare and quantify multifractal objects, appropriate measures such as the Renyi fractal dimension spectrum (RS) and Mandelbrot singularity spectrum (MS) are required. There are two major methods for calculating a singularity spectrum; one is through Legendre transform of the RS, and the other is through the wavelet transform modulus maxima (WTMM) method. This paper provides solutions to the difficulties that arise in the computation of the MS through WTMM, for one-dimensional signals and compares them to the existing multifractal literature and software implementations. Appropriate mother wavelets, continuous wavelet implementation, and thresholding of the wavelet coefficients are also discussed

关键词： Fractals Wavelet analysis Continuous wavelet transforms Wavelet transforms Equations data engineering data compression Laboratories Power engineering computing Aggregates

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A new nonlinear transform for IFS compression of ECG and other signals

A new nonlinear transform for IFS compression of ECG and oth...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： B. Huang W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

Presents a nonlinear extension of the affine transform as used in the iterated function systems (IFS) to compress signals and data. Compared with Oien and Narstad's orthogonal transform with compression ratio of 6.0:1 for the electrocardiogram (ECG) signal, the nonlinear approach produces higher compression ratios of 10.2:1, and is more flexible in finding the corresponding strange attractor of the ECG signal. It can model the QRS complex of the ECG signal well, which has been a problem for the affine transform in fractal compression.

关键词： Electrocardiography Fractals data compression Computational complexity Convergence Laboratories Discrete transforms Image coding Image reconstruction Speech

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Real time 3D animation using progressive transmission

Real time 3D animation using progressive transmission

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： J. Greenberg W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

Current methods of compressing 3D animation for transmission over the Internet tend to be of very low quality. Quality is sacrificed to keep bandwidth low when using lossy compression techniques such as MPEG, Cinepak, or more recent formats such as Vivo and VDOnet. While these techniques can be effective approaches to all-purpose video compression, it should be possible to achieve better performance with the knowledge that the source consists of 3D animation. A new technique is proposed, which instead of focusing on compressing the rendered frames of the animation sequence, compresses and optimizes the original source scene data for streaming, and renders the 3D scene in real time on the client system.

关键词： Animation Layout Image coding Internet Bandwidth Video compression Transform coding data compression Laboratories Streaming media

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Multifractal modelling of arbitrary object boundaries in image segmentation

Multifractal modelling of arbitrary object boundaries in ima...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： S. Siddiqui W. Kinsner Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

This paper addresses the problem of approximation of arbitrary boundaries and edges resulting from image segmentation. Using MPEG-7 terminology, this problem can be considered as the search for a descriptor for a boundary feature of an object. The shape of an object is usually described by its boundaries, to differentiate it from the other regions of the image. Traditionally, Bezier curve fitting has been employed to model the boundaries of objects consisting of smooth and crisp curves. However, natural images contain complex shapes that are difficult to describe by such smooth-boundary modelling techniques. Consequently, we focus on fractals and multifractals to model arbitrary boundaries based on the singularity measure property of fractals. We use wavelets to identify boundary control points and reconstruct the self-similar boundaries with any fractal or multifractal dimension, using the midpoint displacement algorithm.

关键词： Fractals Image segmentation Image coding Shape Curve fitting Video compression MPEG 7 Standard Videoconference Image reconstruction Image storage

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Rotation sensitivity of independent component analysis to outliers

Rotation sensitivity of independent component analysis to ou...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： N. Gadhok W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper evaluates the outlier sensitivity of five independent component analysis (ICA) algorithms (FastICA, extended-infomax, JADE, radical-ICA, and beta-divergence) using (i) the Amari separation performance index, (ii) the optimum angle of rotation error, and (iii) the contrast function difference, in an outlier-contaminated mixture simulation. The Amari separation performance index has revealed a strong sensitivity of JADE and FastICA (using 3rd- and 4th-order nonlinearities) to outliers. However, the two contrast measures demonstrated conclusively that beta-divergence is the least outlier-sensitive algorithm, followed by radical-ICA, FastICA (exponential and hyperbolic-tangent nonlinearities), extended-infomax, JADE, and FastICA (3rdand 4th-order nonlinearities) in an outlier-contaminated mixture of two uniformly distributed signals. The novelty of this paper is the development of an unbiased optimization-landscape environment for assessing outlier sensitivity, as well as the optimum angle of rotation error and the contrast function difference as promising new measures for assessing the outlier sensitivity of ICA algorithms

关键词： Independent component analysis signal processing algorithms Higher order statistics Statistical analysis Robustness Performance analysis Pollution measurement Rotation measurement Source separation data compression

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Robust independent component analysis for cognitive informatics

Robust independent component analysis for cognitive informat...

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IEEE International Conference on Cognitive Informatics

作者： N. Gadhok W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper evaluates the outlier sensitivity of five independent component analysis (ICA) algorithms (FastICA, extended-Infomax, JADE, radical, and /spl beta/-divergence) using: (i) the Amari separation performance index, (ii) the optimum angle of rotation error, and (iii) the contrast function difference, in an outlier-contaminated mixture simulation. The Amari separation performance index has revealed a strong sensitivity of JADE and FastICA, using 3rd- and 4th- order nonlinearities, to outliers. However, the two contrast measures demonstrated conclusively that /spl beta/-divergence is the least outlier-sensitive algorithm, followed by Radical, FastICA (exponential and hyperbolic-tangent nonlinearities), extended-Infomax, JADE, and FastICA (3rd-and 4th-order nonlinearities) in an outlier-contaminated mixture of two uniformly distributed signals. The novelty of this paper is the development of an unbiased optimization-landscape environment for assessing outlier sensitivity, as well as the optimum angle of rotation error and the contrast function difference as promising new measures for assessing the outlier sensitivity of ICA algorithms.

关键词： Robustness Independent component analysis Cognitive informatics Electroencephalography signal processing algorithms Statistical analysis Performance analysis Brain modeling Biomedical measurements Pollution measurement

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Reduced-search fractal block coding of images

Reduced-search fractal block coding of images

引用

data compression Conference (DCC)

作者： W. Kinsner L. Wall Department of Electrical & Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

Summary form only given, as follows. Fractal based data compression has attracted a great deal of interest since Barnsley's introduction of iterated functions systems (IFS), a scheme for compactly representing intricate image structures. This paper discusses the incremental development of a block-oriented fractal coding technique for still images based on the work of Jacquin (1990). A brief overview of Jacquin's method is provided, and several of its features are discussed. In particular, the high order of computational complexity associated with the technique is addressed. This paper proposes that a neural network paradigm known as frequency sensitive competitive learning (FSCL) be employed to assist the encoder in locating fractal self-similarity within a source image. A judicious development of the proper neural network size for optimal time performance is provided. Such an optimally-chosen network has the effect of reducing the time complexity of Jacquin's original encoding algorithm from O(n/sup 4/) to O(n/sup 3/). In addition, an efficient distance measure for comparing two image segments independent of mean pixel brightness and variance is developed. This measure, not provided by Jacquin, is essential for determining the fractal block transformations. An implementation of fractal block coding employing FSCL is presented and coding results are compared with other popular image compression techniques. The paper also present the structure of the associated software simulator.

关键词： Fractals Block codes Image coding Neural networks Power capacitors data compression Computational complexity Frequency Image segmentation Pixel

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