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检索条件"主题词=Compression Algorithms"

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compression of magnetocardiograms using the Discrete Wavelet Transform

Compression of magnetocardiograms using the Discrete Wavelet...

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International Symposium on Electronics and Telecommunications (ISETC)

作者： Beatrice Arvinti Marius Costache Ronny Stolz Department of Physical Foundations of Engineering “Politehnica” University of Timisoara timisoara Romania Department of Quantum Detection Institute of Photonic Technology (IPHT) jena Germany

The paper presents a compression algorithm based on wavelets applied to magnetocardiograms (MCG). MCGs are a newly developed tool for diagnosis of heart diseases, which enable recording of data using sensitive contactless transducers based on Superconductive Interference Devices (SQUID). The acquisition system presented has been developed at the Institute of Photonic Technology (IPHT) in Jena, Germany and several processing techniques based on wavelets have been tested. Wireless technology allows nowadays a remote monitoring of data, and compression techniques have to be developed to enable the storage and handling of a significant quantity of data. A compression technique based on the Discrete Wavelet Transform has been proposed, optimized and its performance evaluated. The method takes into consideration parameters of the input MCG, being thus adaptive. The influence of several features of the algorithm, like mother wavelets, number of vanishing moments, number of decomposition levels, are tested so as to optimize the performances. Results are provided for comparison with other results reported in literature.

关键词： Electrocardiography compression algorithms Discrete wavelet transforms Magnetic recording Superconducting magnets

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Optimization of an electrocardiogram compression technique based on wavelets

Optimization of an electrocardiogram compression technique b...

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International Conference on Optimization of Electrical and Electronic Equipment, OPTIM

作者： Beatrice Arvinti Alexandru Isar Dumitru Toader Marius Costache Physical Foundations of Engineering Polytechnic University of Timisoara Timisoara Romania Faculty of Electronics and Telecommunications Polytechnic University of Timisoara Timisoara Romania

The paper presents the performance of a compression technique designed for electrocardiograms which is of interest due to the actual development of remote monitoring systems. The algorithm is based on wavelets and has been tested on an extended database to outline the performances and enable evaluation. Several features, like class of mother wavelets, number of vanishing moments and quantization level have been taken into consideration, the main aim of the paper being to define an optimization algorithm to allow the implementation of the compression technique in an automated system.

关键词： Electrocardiography Signal to noise ratio Databases Discrete wavelet transforms compression algorithms Optimization Distortion measurement

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Mother wavelet selecting method for selective mapping technique ECG compression

Mother wavelet selecting method for selective mapping techni...

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International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Yotaka Chompusri Kobchai Dejhan Surapun Yimman Faculty of Engineering King Mongkut's Institute of Technology Ladkmbang Thailand Faculty of Applied Science King Mongkuts University of Technology North Bangkok Thailand

The electrocardiogram compression method presented in this research processes the residual signal which is the difference between the original signal and the reference signal. The residual signal is transformed to wavelet domain and then the redundant information is eliminated in wavelet domain. The selection of mother wavelet is one of main factor to maintain the important data in wavelet domain. The difference type of mother wavelet has its own shape and its own characteristic. Therefore this affects to the performance of compression. This work compares the efficiency of compression algorithm by using difference type of Mother Wavelet. The test shows that no mother wavelet which is the best for all ECG. Thereby, reducing the time consuming for selection the proper mother wavelet, the Best of Four Method is introduced. This algorithm uses four types of mother wavelet to be competitors, `db1', `db2', `db9' and `bior2.4'. The result shows that the selected mother wavelet types have the good performance on overall tested signals. Moreover, the `db1' mother wavelet has the best performance on more than a half of all signals.

关键词： Electrocardiography Wavelet domain Biomedical engineering Discrete wavelet transforms compression algorithms

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Multi-channel EEG compression based on 3D decompositions

Multi-channel EEG compression based on 3D decompositions

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Justin Dauwels Srinivasan K. Ramasubba Reddy M. Andrzej Cichocki Nanyang Technological University Singapore Indian Institute of Technology Madras Chennai India Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Wako Japan RIKEN BSI Laboratory for Advanced Brain Signal Processing Wako-Shi Japan

Various compression algorithms for multi-channel electroencephalograms (EEG) are proposed and compared. The multi-channel EEG is represented as a three-way tensor (or 3D volume) to exploit both spatial and temporal correlations efficiently. A general two-stage coding framework is developed for multi-channel EEG compression. In the first stage, we consider (i) wavelet-based volumetric coding; (ii) energy-based lossless compression of wavelet subbands; (iii) tensor decomposition based coding. In the second stage, the residual is quantized and coded. Through such two-stage approach, one can control the maximum error (worst-case distortion). Numerical results for a standard EEG data set show that tensor-based coding achieves lower worst-case error and comparable average error than the wavelet- and energy-based schemes.

关键词： Electroencephalography Encoding Tensile stress Correlation Image coding Wavelet transforms compression algorithms

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Applying Radiation Hardening by Software to Fast Lossless compression Prediction on FPGAs

Applying Radiation Hardening by Software to Fast Lossless Co...

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IEEE Aerospace Conference

作者： Andrew G. Schmidt John Paul Walters Kenneth M. Zick Matthew French Didier Keymeulen Nazeeh Aranki Matthew Klimesh Aaron Kiely Information Sciences Institute University of Southern California Jet Propulsion Laboratory California Institute of Technology

ISBN: (纸本)9781457705564

As scientists endeavor to learn more about the world's ecosystems, engineers are pushed to develop more sophisticated instruments. With these advancements comes an increase in the amount of data generated. For satellite based instruments the additional data requires sufficient bandwidth be available to transmit the data. Alternatively, compression algorithms can be employed to reduce the bandwidth requirements. This work is motivated by the proposed HyspIRI mission, which includes two imaging spectrometers measuring from visible to short wave infrared (VSWIR) and thermal infrared (TIR) that saturate the projected bandwidth allocations. We present a novel investigation into the capability of using FPGAs integrated with embedded PowerPC processors to adequately perform the predictor function of the Fast Lossless (FL) compression algorithm for multispectral and hyperspectral imagery. Furthermore, our design includes a multi-PowerPC implementation which incorporates recently developed Radiation Hardening by Software (RHBSW) techniques to provide software-based fault tolerance to commercial FPGA devices. Our results show low performance overhead (4-8percent) while achieving a speedup of 1.97X when utilizing both PowerPCs. Finally, the evaluation of the proposed system includes resource utilization, performance metrics, and an analysis of the vulnerability to Single Event Upsets (SEU) through the use of a hardware based fault injector.

关键词： Radiation hardening Field programmable gate arrays compression algorithms computer software bandwidth allocation Single event upsets lossless compression Speeding Fault tolerance Engineers imaging spectrometers

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A Segmentation Progressive Mesh compression Method

A Segmentation Progressive Mesh Compression Method

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International Conference on Audio, Language and Image Processing

作者： Haifeng Yu Junli Chen Wanggen Wan Rui Wang Xiaoqing Yu School of Communication and Information Engineering Shanghai University

ISBN: (纸本)9781467301732

The progressive mesh compression algorithm on the blocks of model based on edge-collapse mesh simplification is proposed to solve some practical problems. At first, we adopt K-means to cluster the mesh triangles. Secondly, we compress each model block. The detail information of different groups obtained by compressing each of blocks are independent of each other. If some details are lost in transmission, other details can also decode independently. We only need to request server to resend the lost part of the groups data. At the same time, it can be decoded regional details depend on our viewpoint when we need to had the complex models. Because our vision can only focus on part region of model, and the area in which we isn 't interested can be instead by coarse model.

关键词： progressive mesh COMPRESSED compression algorithms Servers Comment Sight Blocks

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Assessing the Impact of Network compression on Molecular Dynamics and Finite Element Methods

Assessing the Impact of Network Compression on Molecular Dyn...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Branimir Dickov Miquel Pericàs Guillaume Houzeaux Nacho Navarro Eduard Ayguadé Universitat Politècnica de Catalunya Spain Barcelona Supercomputing Center Spain Tokyo Institute of Technology Japan

Efficient communication in parallel applications is one of the main challenges for the scalability of supercomputers, both in weak and strong scaling environments. In the past, several compression techniques have been proposed as a way to improve the performance and scalability of parallel applications. Those works have shown significant speed-ups when applying compressors to the MPI transfers of certain algorithmic kernels. However, these techniques have not seen widespread adoption in current supercomputers. This paper evaluates the bottlenecks of network compression that have precluded their generalized adoption in HPC environments. In order to evaluate their impact on real applications we integrated multiple MPI compression schemes into two production applications: a computational mechanics code dominated by point-to-point communication, and a molecular dynamics code dominated by collective communications. While the applications observe some improvements when applying aggressive lossy compression schemes on systems ranging from 4 to 256 processors, the overall results seem to contradict earlier research. We conclude that HPC data traffic tends to be too statistically random to be captured by general lossless compressors, and that the size of MPI message is most often not the limiting component of these communication-bound applications. We also observed that aggressive lossy compression worked well and did not distort the results of the evaluated applications. This suggests that reducing network bandwidth in conjunction with message compression may be an interesting technique to increase energy efficiency in HPC systems.

关键词： Program processors Kernel Compressors compression algorithms Accuracy Bandwidth Scalability

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An ECG compression Algorithm Based on Gradient Difference for Body Sensor Networks

An ECG Compression Algorithm Based on Gradient Difference fo...

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International Conference on Biomedical Engineering and Biotechnology (iCBEB)

作者： Yuangui Zhang Y.T. Zhang Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Key Laboratory for Health Informatics Chinese Academy of Sciences Shenzhen China Joint Research Centre for Biomedical Engineering Department of Electronic Engineering The Chinese Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Key Laboratory for Health Informatics Chinese Academy of Science University of Hong Kong Sha Tin Hong Kong China

We propose a novel scheme for ECG compression based on Gradient difference used in BSN. As a newly emerged application, BSN can continuously monitor the patients' physiological signal without hindering their everyday life, however, it has some constraints, namely, size, power, capability of storage and computation. ECG is a nontrivial signal collected by BSN, continuous collection will bring huge data flow which is a burden both to sensor nodes and central node, therefore we have to do some compression to relieve the burden. As the constraints exist, most of the traditional algorithms are not adaptive enough, we need a simple, real-time and effective approach. This paper introduces an approach to meet those requirements, by conducting various experiments, we found that this approach can effectively compress ECG signal and meanwhile keep a good fidelity of the reconstructed signal, to prove that, we did some compare between our approach and traditional ones. Yet, this algorithm has not been tested on the clinical ECG signals and there is still room for the performance improvement.

关键词： Electrocardiography Redundancy Biomedical monitoring compression algorithms Data compression Biomedical engineering Monitoring

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compression of GPS trajectories using optimized approximation

Compression of GPS trajectories using optimized approximatio...

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International Conference on Pattern Recognition

作者： Minjie Chen Mantao Xu Pasi Fränti University of Eastern Finland Finland Shanghai Dianji University China

ISBN: (纸本)9781467322164

A large number of GPS trajectories, which include users' spatial and temporal information, are collected by geo-positioning mobile phones in recent years. The massive volumes of trajectory data bring about heavy burdens for both network transmission and data storage. To overcome these difficulties, GPS trajectory compression algorithm (GTC) was proposed recently that optimizes both the data reduction by trajectory simplification and the coding procedure using the quantized data. In this paper, instead of using greedy solution in GTC algorithm, the approximation process is optimized jointly with the encoding step via dynamic programming. In addition, Bayes' theorem is applied to improve the robustness of probability estimation for encoded values. The proposed solution has the same time complexity with GTC algorithm in the decoding procedure and experimental results show that its bitrate is around 80% comparing with GTC algorithm.

关键词： Trajectory Global Positioning System Encoding Approximation methods Image coding Time complexity compression algorithms

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compression scheme for increasing the lifetime of wireless intelligent sensor networks

Compression scheme for increasing the lifetime of wireless i...

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European Signal Processing Conference (EUSIPCO)

作者： Dragos Ioan Sacaleanu Rodica Stoian Dragos Mihai Ofrim Nikos Deligiannis Faculty of Electronics Telecommunications and Information Technology Universitatea Politehnica din Bucuresti Bucharest Romania Department of Electronics and Informatics Vrije Universiteit Brussel Brussels Belgium Interdisciplinary Institute for BroadBand Technology Ghent Belgium

Wireless intelligent sensor networks (WISN) are characterized by the ability of self-organization and autocoordination for long periods of time. In most cases, the limitation of time function is given by the energy supply of the sensors. Taking into account that the greatest amount of energy is spent in transmission, many studies are concentrated on minimizing the amount of transmitted bits. In order to perform this, data compression algorithms are introduced in data processing. This paper presents a scheme that combines a new extrapolation prediction algorithm and a simple Huffman compression algorithm in order to prolong the lifetime of the WISN. Compared with other data compression schemes, the new scheme has obtained better experimental results in terms of number of bits transmitted and compression ratio.

关键词： Prediction algorithms Heuristic algorithms Sensors Wireless sensor networks Data compression Extrapolation compression algorithms

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