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Multifractal characterization of electromyogram signals

Multifractal characterization of electromyogram signals

引用

Canadian Conference on electrical and computer engineering (CCECE)

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

Surface electromyography is a useful means of studying normal and abnormal muscle functions and has many applications, including pathological diagnosis and prosthetic control. Most of the studies of such electromyogram (EMG) signals are based on either the analysis of their stochastic temporal characteristics in the time domain, or the power spectrum characteristics in the frequency domain. In this paper, we present an approach to characterization and feature extraction of EMG signals. This approach is based upon the chaotic behaviour of the EMG signals and the existence of the corresponding strange attractors with low embedding dimensions. The multifractal dimensions of the strange attractors underlying the chaos provide alternative features for analyzing the EMG signals, and describe how the entropy of these strange attractors changes as the hypervolume scales used for calculating the entropy vary.

关键词： Fractals Electromyography signal analysis Chaos Entropy Muscles Pathology Prosthetics Stochastic processes Time domain analysis

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Multifractal wavelet compression of fingerprints

Multifractal wavelet compression of fingerprints

引用

Communications, Power and Computing Conference: WESCANEX

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

This paper presents compression of grey-scale fingerprint images, using a wavelet transform guided by a multifractal measure to obtain the best reconstructed image in terms of a higher peak signal to noise ratio, PSNR, at the lowest bit rate. The fingerprint images and the corresponding wavelet coefficients are considered to be approximation of strange attractors and can be analyzed by their multifractality. The wavelet can provide not only the grouping of subbands information and the highest compression for optimum bit allocation (quantization), but also an optimum synthesis (combination of subbands) by the inverse wavelet transform to achieve the highest image quality. The motivation for this paper is to find the best combination of the subbands for both the quantization and image quality by applying the Mandelbrot (1983) singularity measure to the coefficients in various subbands.

关键词： Fractals Fingerprint recognition Image coding Image matching Wavelet transforms PSNR Bit rate Quantization Image quality Noise measurement

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Fractal segmentation of signal from noise for radio transmitter fingerprinting

Fractal segmentation of signal from noise for radio transmit...

引用

Canadian Conference on electrical and computer engineering (CCECE)

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

This paper presents a study of segmentation between channel noise and turn-on transient for radio transmitter fingerprinting. The segmentation is based on a multifractal measure, which is called variance fractal dimension trajectory. Previous studies have shown that this multifractal measure is effective in nonstationary signal characterization. We employ two techniques for the variance fractal dimension implementation and evaluate them in terms of noise segmentation. An optimal window size for the fingerprinting is presented. We also present the Renyi dimension trajectory based on generalized entropy as an alternative of the variance fractal dimension measure for noise segmentation.

关键词： Fractals Radio transmitters Fingerprint recognition Entropy Noise measurement Sun data compression Laboratories signal analysis

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signal separation by independent component analysis and fuzzy estimators

Signal separation by independent component analysis and fuzz...

引用

Conference of the North American Fuzzy Information Processing Society - NAFIPS

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

Independent component analysis (ICA) is a developing field of interest for researchers in signal processing and artificial neural networks. ICA is an "intelligent signal processing" extension to the principal component analysis that becomes sensitive to non-Gaussian higher-order statistics. This paper presents the motivation of ICA and a treatment of the theory with a guiding example. The limitations of current ICA algorithms are discussed in general and the possible benefits of developing fuzzy engines as ICA estimators are discussed. In particular, a Mamdani-type fuzzy inference system for determining an optimal ICA rotation of whitened two-dimensional uniform noise is implemented as an example of the feasibility of this new direction in ICA.

关键词： Source separation Independent component analysis signal processing algorithms Artificial neural networks Artificial intelligence Principal component analysis Higher order statistics Inference algorithms Engines Fuzzy systems

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Surrogate ECG signals for the null-hypothesis analysis of heart monitoring

Surrogate ECG signals for the null-hypothesis analysis of he...

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Canadian Conference on electrical and computer engineering (CCECE)

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

This paper introduces a class of synthetic electrocardiograms (ECG) for the purpose of testing the sensitivity and robustness of heart-monitoring techniques in controlled and reproducible simulations. These ECG surrogates are constructed by adapting an existing standard ECG synthesizer to act as a modulator on a tachogram input, enabling null-hypothesis analysis on heart-rate variability. This establishes an empirical link between the tachogram literature and the design of heart monitoring techniques. The new methodology is demonstrated experimentally and its performance is discussed

关键词： Electrocardiography signal analysis Heart

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ECG frame classification using dynamic time warping

ECG frame classification using dynamic time warping

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Canadian Conference on electrical and computer engineering (CCECE)

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

Presents an electrocardiogram (ECG) frame classification technique realized by a dynamic time warping (DTW) matching technique, which has been used successfully in speech recognition. We use the DTW to classify ECG frames because ECG and speech signals have similar nonstationary characteristics. The DTW mapping function is obtained by searching the frame from its end to start. A threshold is setup for DWT matching residual either to classify an ECG frame or to add a new class. Classification and establishment of a template set are carried out simultaneously. A frame is classified into a category with a minimal residual and satisfying a threshold requirement. A classification residual of 1.33% is achieved by the DTW for a 10-minute ECG recording.

关键词： Electrocardiography Heart beat Fluctuations Rhythm Speech recognition Timing data compression Laboratories Discrete wavelet transforms Electrodes

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compression of multifractal object boundaries: a comparison of two approaches

Compression of multifractal object boundaries: a comparison ...

引用

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 presents a comparative study of two approaches that address the problem of compression of arbitrary object boundaries resulting from image segmentation. The first approach uses multiresolution based techniques, in which the boundary is represented compactly by two sets of descriptors and control points which are obtained by applying wavelet and fractal analysis. The midpoint displacement algorithm is then applied to the two sets of control points in order to reconstruct the boundaries with the required fractal dimension. The second approach is based on the iterated function system (IFS). In this approach, the object boundary is regarded as an attractor of an IFS having the same Renyi fractal dimension spectrum as the original boundary. The experimental results show that the multifractal object boundaries can be modelled compactly using both approaches. The compression ratio achieved for the wavelet-based approach was 285:1, while for the IFS-based approach it was 52:1. These results can be compared with state of the art image compression techniques such as JPEG2000

关键词： Fractals Image coding Image segmentation Transform coding Video compression Shape Curve fitting data compression Laboratories signal resolution

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Feature extraction from DNA sequences by multifractal analysis

Feature extraction from DNA sequences by multifractal analys...

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

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

This paper presents feature extraction and estimation of multifractal measures of DNA sequences, using a multifractal methodology, and demonstrates a new scheme for identifying biological functionality, using information contained within the DNA sequences. It shows that the Renyi and Mandelbrot fractal dimension spectra may be useful techniques for extracting the information contained in the DNA sequences.

关键词： Feature extraction DNA Sequences Fractals Genomics Bioinformatics Organisms Proteins Humans Amino acids

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Multifractal analysis of transients in power systems

Multifractal analysis of transients in power systems

引用

Canadian Conference on electrical and computer engineering (CCECE)

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

This paper presents the variance fractal dimension trajectory (VFDT) approach to studying nonstationary transients in power system. Experiments show that multifractal analysis based on the VFDT is efficient for characterizing most of the transient types found in power system signals and data reduction can be realized by simply changing the window displacement. In addition, analysis of transient signals contaminated by noise shows that the VFDT approach is very immune to noise.

关键词： Transient analysis Power system transients Fractals Power system analysis computing Discrete wavelet transforms signal analysis Electromagnetic transients data compression Capacitors Fourier transforms

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Perceptual image compression through fractal surface interpolation

Perceptual image compression through fractal surface interpo...

引用

Canadian Conference on electrical and computer engineering (CCECE)

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

This paper presents a perceptual image compression technique using fractal surface interpolation (FSI). This technique relies on the extraction and reconstruction of self-affine fractal surfaces with a specified Hurst exponent H*. Fractional Brownian motion (fBm) through midpoint displacement (MPD) provides the basis for generating these fractal surfaces between interpolation points. The MPD algorithm is designed to eliminate creasing often associated with MPD in two dimensions. Experimental results show that when applied to 512/spl times/512 8-bit gray-level images, perceptually good results are achieved with a bit rate of 0.35 bpp.

关键词： Image coding Fractals Interpolation Surface treatment Brownian motion Image generation data compression Laboratories data mining Algorithm design and analysis

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