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Wavelet-based ECG signals compression using SPIHT technique and VKTP coder

Wavelet-based ECG signals compression using SPIHT technique ...

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international conference on signals, Circuits and Systems, SCS

作者： N. Boukhennoufa K. Benmahammed M. A. Abdi F. Djeffal Department of Electronics University of Batna Batna Algeria Department of Electronics Setif Algeria

ISBN: (纸本)9781424443970;9781424443987

In this paper, an efficient Electrocardiogram (ECG) signal compression method based on wavelet transform is presented. The proposed method combines the adapted SPIHT (Set Partitioning In Hierarchical Trees) method with VKTP (Vector K-Tree Partitioning) coder. The SPIHT method is based on the use of wavelet transform which is very well suited to locate the energy of the signal in fewer coefficients. Using the VKTP algorithm, to encode the generated bit stream of SPIHT algorithm, we achieve high compression performances. The tests of this lossy compression/ decompression technique are performed on many ECG records from Arrhythmia database. The obtained results illustrate the capabilities of the proposed approach to improve the compression ratio while maintaining a good signal quality.

关键词： Electrocardiography Discrete wavelet transforms Fourier transforms Partitioning algorithms Discrete cosine transforms Discrete Fourier transforms Wavelet transforms signal processing algorithms data compression Information analysis

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Classification Method of EEG signals Based on Wavelet Neural Network

Classification Method of EEG Signals Based on Wavelet Neural...

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international conference on Bioinformatics and Biomedical Engineering (ICBBE)

作者： Hongyu Sun Yang Xiang Yinjing Guo Sch. of Electron. & Inf. Eng. Tongji Univ. Shanghai China Shandong University of Science and Technology

A new wavelet neural network (WNN) is constructed combining wavelet transform and neural network theory to classify electroencephalogram (EEG) signals. The new WNN takes nonlinear mother wavelet as neuron instead of traditional nonlinear sigmoid function. It owns the merits of good generalization ability and high converging speed. In addition, multi-resolution and self-adaptation are also its advantages. Experimental results have shown that our method performs well for the classification of mental tasks from EEG data compared with the approaches based on traditional neural network. It can provide a new way for the EEG automation classification when the EEG is used as input signal to a brain computer interface (BCI).

关键词： Electroencephalography Neural networks Biological neural networks Electrodes Brain computer interfaces signal processing Humans Artificial neural networks Wavelet transforms Educational institutions

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Online prediction model based on Reduced Kernel Principal Component Analysis

Online prediction model based on Reduced Kernel Principal Co...

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international conference on signals, Circuits and Systems, SCS

作者： Okba Taouali Ilyes Elaissi Hassani Messaoud Traitement de Signal et Image ATSI Unitéde Recherche d'Automatique Monastir Tunisia

ISBN: (纸本)9781424443970;9781424443987

This paper proposes a new technique for online identification of a nonlinear system modeled on reproducing kernel Hilbert space (RKHS) using kernel method. This new method uses the reduced kernel principal component analysis (RKPCA) to update the principal component which represent the observations selected by the kernel principal component analysis method (KPCA). The KPCA is a nonlinear extension of principal component analysis (PCA) to RKHS as it transforms the input data by a nonlinear mapping from the input space into a high dimensional feature space to which the PCA is performed. The proposed technique may be very helpful to design an adaptive control strategy of nonlinear systems.

关键词： Predictive models Kernel Principal component analysis Hilbert space Nonlinear systems signal processing Covariance matrix Circuits and systems Adaptive control Statistical learning

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Development of a novel instrument based on DSP for measuring vehicle noise combined with engine rotating speed

Development of a novel instrument based on DSP for measuring...

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international conference on Power Electronics Systems and Applications (ICPESA)

作者： Xiao-yu Lei Guang-zhong Cao College of Mechatronics and Control Engineering Shenzhen University Shenzhen China

In order to measure vehicle's noise and the engine speed, a novel instrument is developed based on digital signal processor DSP-TMS320VC33 and monolithic processor AT89C51. The DSP is mainly used to process the data and the monolithic processor is used for human-machine interface and management. The new idea applies non-contact measurement of vehicle noise by the microphone to extract the vehicle engine speed. By using noise reduction method based on Wavelet Transform, vehicle engine speed information is picked up from the noise at the outlet of vehicle exhaust pipe. The developed instrument can meet the practical measurement requirements with measuring speed scope within 30~8000 rpm and the error within 10 rpm, the measured noise rang is 30~130 dB and the resolution ratio is 0.1 dB.

关键词： Instruments Digital signal processing Rotation measurement Velocity measurement Noise measurement Vehicles Engines Noise reduction Digital signal processors Man machine systems

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Canal9: A database of political debates for analysis of social interactions

Canal9: A database of political debates for analysis of soci...

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international conference on Affective Computing and Intelligent Interaction and Workshops, ACII

作者： A. Vinciarelli A. Dielmann S. Favre H. Salamin Idiap Research Institute Martigny Switzerland Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland

Automatic analysis of social interactions attracts major attention in the computing community, but relatively few benchmarks are available to researchers active in the domain. This paper presents a new, publicly available, corpus of political debates including not only raw data, but a rich set of socially relevant annotations such as turn-taking (who speaks when and how much), agreement and disagreement between participants, and role played by people involved in each debate. The collection includes 70 debates for a total of 43 hours and 10 minutes of material.

关键词： Irrigation databases Audio recording signal processing Cameras Privacy Broadcasting Licenses Statistics Protocols

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Automatic data processing to Relative Quantitative Analysis of 1H MR Spectroscopy of Brain

Automatic Data Processing to Relative Quantitative Analysis ...

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The 3rd international conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

作者： Shuai WANG Weibei DOU Jean-Marc CONSTANS Shaowu LI Tsinghua National Laboratory for Information Science and Technology Dept.of Electronic Engineering T Unité d'IRM EA3916CHRU CaenFrance Neuroimaging Center of Tiantan Hospital Capital Medical University Beijing P.R.China

This paper presents an automatic method for processing the data of 1H magnetic resonance spectroscopy. This method focuses on expressing the metabolites concentration ratios of the brain, such as NAA/Cr, NAA/Cho, Cho/Cr, etc. The data processing system consists of water suppression with wavelet basis function, automatic coefficients selection of the Gaussian transform based on the signal characteristics and experience formulas. Especially, our automatically relative quantitative analysis is based on an approximate method to label the chemical shift in parts per million (ppm) in the case of some necessary information are missed, such as the sampling rate and reference resonance frequency. It is very useful in the fusion system of brain tumor features extracted from MR images and MR spectrum.

关键词： MR Spectroscopy brain relative quantification chemical shift metabolite concentration wavelat fusion

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A theoretical study of error mechanisms in switched-current circuits

A theoretical study of error mechanisms in switched-current ...

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international conference on signals, Circuits and Systems, SCS

作者： Karim Abbes Mohamed Masmoudi Electronics Microtechnology and Communication (EMC) Research Group National Engineering School of Sfax (ENIS) Sfax Tunisia

This paper describes a theoretical study of the main errors in switched-current (SI) cells, such as conductance ratio error, settling time error and charge injection error, and their influence on the output/input transfert characteristic. First, our interest is focused on the study each error mechanism and its effect on the SI memory cell. After that, we studied the influence of their cumulative effect. Finally, we detailed the effect of cumulative error on the integrator level. The most significant non-idealities of SI cell are identified and their cumulative effect on SI cell and SI integrator transfert characteristic are analytically demonstrated.

关键词： Switching circuits Circuits and systems Communication switching Analog-digital conversion Clocks Voltage Electromagnetic compatibility Delay signal processing data conversion

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Sigma-Delta Receive Beamformer Based on Cascaded Reconstruction for Ultrasound Imaging Application

Sigma-Delta Receive Beamformer Based on Cascaded Reconstruct...

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international conference on Bioinformatics and Biomedical Engineering (ICBBE)

作者： Jia Hao Cheong Yvonne Ying Hung Lam Liang Mong Koh Kei Tee Tiew Division of Circuits and Systems Nanyang Technological University Singapore Nanyang Technological University Singapore Singapore SG

A pre-delay reconstruction sigma-delta beamformer (SDBF) was recently proposed to achieve higher level of integration in ultrasound imaging system. Nevertheless, the high order reconstruction filter used in each channel of SDBF makes the beamformer highly complex. The beamformer can be simplified by reconstructing the signal after the delay-and-sum process with only one filter. However, this post-delay reconstruction-based design degrades image quality when dynamic focusing is performed. This paper shows that employing simple pre-delay filter is sufficient to achieve similar performance as conventional pre-delay reconstruction SDBF, as long as the pre-delay filter provides the required pre-delay signal-to-quantization noise ratio (SQNR). Based on this finding, we proposed a cascaded reconstruction beamformer which utilizes a boxcar filter as the pre-delay filter in each channel. Simulations using real phantom data demonstrate that the proposed beamforming method can achieve a contrast resolution comparable to that of the pre-delay reconstruction beamforming method. Besides, the hardware can also be greatly simplified compared to the pre-delay reconstruction beamformers.

关键词： Ultrasonic imaging Delta-sigma modulation Image reconstruction Filters Array signal processing signal processing Delay Degradation Image quality Focusing

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Feature selection and construction for the discrimination of neurodegenerative diseases based on gait analysis

Feature selection and construction for the discrimination of...

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international conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth

作者： Mingjing Yang Huiru Zheng Haiying Wang Sally McClean Faculty of Computing and Engineering University of Ulster UK

Gait disorder is one symptom of neurodegenerative disease. Using wearable motion sensors to monitor the motor function of patients with neurodegenerative disease has attracted more attention. Research has shown that machine learning techniques can be applied to the classification of neurodegenerative diseases from the gait data recorded by footswitches. In order to identify the most valuable features from 10 raw temporal variables extracted from gait cycles to improve the classification performance, we examine four types of feature selection and construction methods, namely, maximum signal-to-noise ratio based feature selection method, maximum signal-to-noise ratio combined with minimum correlation based feature selection method, maximum prediction power combined with minimum correlation based feature selection method and principal component analysis. Results show that using a set of four features, a relatively high prediction performance has been achieved with classification accuracies ranging from 79.04% to 93.96%. The continual increase of the number of features does not significantly contribute to the improvement of classification performance. This is consistent with clustering-based feature analysis.

关键词： Parkinson's disease Biomedical monitoring Wearable sensors Patient monitoring Machine learning Backpropagation Legged locomotion data mining signal processing Support vector machines

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DWT based on watermarking algorithm and its implementing with DSP

DWT based on watermarking algorithm and its implementing wit...

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IEEE international Workshop on Anti-counterfeiting, Security, Identification, ASID

作者： Qiwei Lin Zhenhui Liu Gui Feng Department of Electronic and Communication HuaQiao University Quanzhou China

A novel adaptive watermarking algorithm is presented in this paper. At the same time, how to transplant this watermarking system to the DSP platform was introduced. The watermarking scheme is based on image wavelet transform domain. First, we decompose the carrier image into 4 sub-bands. Then according to HVS, we adaptively select some low frequencies coefficients to embed watermark data. For the security of watermarking system, the watermark image is disordered according the chaos sequence. In the watermark extracting step, we can extract watermark image without the initial carrier image, so the blind scheme was obtained. The experimental results show that the proposed watermarking scheme is robust to most attacks. After testing the watermarking scheme, we transplant the watermarking system to TMS320C6416 Platform. This makes the watermarking system is possible for practical usages.

关键词： Discrete wavelet transforms Watermarking Digital signal processing data mining Wavelet domain Wavelet transforms Frequency data security Chaos Robustness

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