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International Conference on Electronics and Information Technology (EIT)

作者： Sadchenko, A. Kushnirenko, O. Plachinda, O. Odessa Natl Polytech Univ Dept Elect Telecommun Syst Odessa Ukraine Odessa Natl Polytech Univ Dept Petr & Chem Engn Odessa Ukraine

ISBN: (纸本)9781509022267

The authors propose a fast lossy compression algorithm for medical image compression. This algorithm has been designed taking into account the peculiarities of medical images. The uniform distribution of errors is applied. A comparative analysis of the proposed algorithm with known compression algorithms which use the wavelet transform is performed. The simulation results confirm the high efficiency of the proposed algorithm.

关键词： medical image processing lossy compression algorithm wavelet transform

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Deterministic Search Strategy of compression Codes 26

Deterministic Search Strategy of Compression Codes

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26th Euromicro Conference on Digital System Design (DSD) / 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

作者： Novak, Ondrej Tech Univ Liberec Inst Informat Technol & Elect Liberec Czech Republic

ISBN: (纸本)9798350344196

Testing large circuits requires compression of test patterns before transferring them to the tested circuit and decompression on board. The compression and decompression mechanism may be built according to the linear block code rules. Broadening the decompressor structure search space to those using nonlinear block code is possible. Nonlinear block codes outperform their linear counterparts' compression ability. Their usage is limited due to the intricate search process. The code words' interconnectedness is difficult to exploit in the code word creation process as too many mutual dependencies exist among the code word bits. For this reason, random and partially random code word search methods were investigated in the past. This paper proposes two fully deterministic nonlinear code construction approaches. The obtained codes are significantly more efficient and easily scalable than the linear ones. We demonstrate their efficiency on codes with the number of specified bits equal to two, three, and four. The proposed methods may be used to create extensive codes, which are unachievable for previously published methods due to the explosion of computation time.

关键词： lossy compression algorithm Test vector compression Pseudo-exhaustive testing Binary nonlinear codes Graph theory Minimum clique cover problem Design for testability

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Low-loss image-based compression for synchrophasor measurements

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第20期14卷 4571-4579页

作者： Acharya, Sowmya DeMarco, Christopher L. Univ Wisconsin Dept Elect & Comp Engn 1415 Johnson Dr Madison WI 53706 USA

Deployments of high-sampling rate synchronised phasor measurement units (PMUs) are growing rapidly throughout the world, and with the advent of microPMUs, spreading from bulk transmission through distribution systems. The growing volume of PMU data presents challenges in its communication and storage, motivating consideration of compression algorithms. This study presents a novel lossy compression algorithm that exploits particular characteristics of power system measurements to improve the compression. Concepts successfully applied in image compression are tailored to the spatio-temporal correlations induced between electrical quantities via their network interconnections. The quality of the resulting compression is judged on the balance of storage space savings versus the accuracy of data reconstruction. In representative real-world and transient simulation datasets, the technique developed can provide storage compression in the range of 40:1 when different physical quantities are compressed together. The compression ratios can be in the range of 90:1 for voltage magnitudes and 190:1 for frequency when the measurements are compressed separately. The high-compression ratios are achieved while maintaining low-loss (high-accuracy) reconstruction.

关键词： phasor measurement data compression power system measurement image coding synchronisation power engineering computing distribution networks low-loss image-based compression synchrophasor measurements high-sampling rate distribution systems PMU data lossy compression algorithm power system measurements image compression spatio-temporal correlations data reconstruction storage compression high-compression ratios synchronised phasor measurement units

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Multiple Leads With a Switch Mode for Lossless and lossy compression Using Very-Large-Scale Integratinn Technology

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IEEE ACCESS 2018年 6卷 67291-67300页

作者： Tseng, Yun-Hua Chen, Yuan-Ho Lu, Chih-Wen Natl Tsing Hua Univ Dept Engn & Syst Sci Hsinchu 30013 Taiwan Chang Gung Univ Dept Elect Engn Taoyuan 33302 Taiwan Chang Gung Mem Hosp Dept Radiat Oncol Linkou 33305 Taiwan

Electrocardiogram monitoring is crucial for the prevention and treatment of cardiovascular diseases. In this paper, we developed a wearable device involving multiple leads that monitors cardiac electrical activity using very large-scale integration technology to facilitate long-term activity monitoring. In addition to using limb leads and augmented limb leads for monitoring heart activity, six unipolar chest leads were attached to six positive electrodes and placed on the surface of the chest to record electrical activity of different regions of the heart. The multiple leads lie perpendicular to the frontal plane and were integrated within a single circuit to reduce hardware costs and size of the device. The proposed architecture also allows users to switch between lossless and lossy compression to control the power consumption and bit compression ratio. The effectiveness of the proposed approach was verified by fabricating a chip using 0.18-mu m CMOS technology. The proposed architecture core has an operating frequency of 41 MHz and a gate count of 4K.

关键词： Electrocardiogram (ECG) multiple leads lossless compression algorithm lossy compression algorithm bit compression ratio

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Efficient compression algorithm with Limited Resource for Continuous Surveillance

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2016年第11期10卷 5476-5496页

作者： Yin, Ling Liu, Chuanren Lu, Xinjiang Chen, Jiafeng Liu, Caixing South China Agr Univ Coll Math & Informat Guangzhou Guangdong Peoples R China Drexel Univ Dept Decis Sci & Management Informat Syst Philadelphia PA 19104 USA Northwestern Polytech Univ Sch Comp Sci Xian Peoples R China

Energy efficiency of resource-constrained wireless sensor networks is critical in applications such as real-time monitoring/surveillance. To improve the energy efficiency and reduce the energy consumption, the time series data can be compressed before transmission. However, most of the compression algorithms for time series data were developed only for single variate scenarios, while in practice there are often multiple sensor nodes in one application and the collected data is actually multivariate time series. In this paper, we propose to compress the time series data by the Lasso (least absolute shrinkage and selection operator) approximation. We show that, our approach can be naturally extended for compressing the multivariate time series data. Our extension is novel since it constructs an optimal projection of the original multivariates where the best energy efficiency can be realized. The two algorithms are named by ULasso (Univariate Lasso) and MLasso (Multivariate Lasso), for which we also provide practical guidance for parameter selection. Finally, empirically evaluation is implemented with several publicly available real-world data sets from different application domains. We quantify the algorithm performance by measuring the approximation error, compression ratio, and computation complexity. The results show that ULasso and MLasso are superior to or at least equivalent to compression performance of LTC and PLAMlis. Particularly, MLasso can significantly reduce the smooth multivariate time series data, without breaking the major trends and important changes of the sensor network system.

关键词： lossy compression algorithm fused lasso wireless sensor network energy efficiency

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Sound Data compression Using Different Methods

Sound Data Compression Using Different Methods

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4th ObCom International Conference on Recent Trends in Computing, Communication and Information Technology

作者： Kumbhar, Pravin Y. Krishnan, Shoba Mumbai Univ Dept Elect & Telecommun Vivekanand Educ Soc Inst Technol Bombay Maharashtra India

ISBN: (纸本)9783642292187

This paper is about the methods of sound data compression. The development of audio data compression has significantly made our lives easier. The technological progress has facilitated the process of recording audio on different media such as CD-Audio. In recent years. much has been achieved in the field of audio and speech compression. Many standards have been established In order to compare methods of sound data compression I have used Adobe Audition 3.0 software and computer program of the sound compression system from manufacturers' side. They are characterized by more better sound quality at lower bit rate. It allows recording the same CD-Audio formats using "lossy" or lossless compression algorithms in order to reduce the amount of data surface area at almost noticeable difference in the quality of the recording. To illustrate the problem, I have used the graphs of the spectrum and musical composition spectrograms. The comparison has been done on the basis of uncompressed music track from the original CD-Audio) lines before and after the abstract. This document is in the required format.

关键词： sound data compression mp3 FLAC Lossless compression algorithm lossy compression algorithm

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The effect of lossy ECG compression on QRS and HRV feature extraction

The effect of lossy ECG compression on QRS and HRV feature e...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Twomey, Niall Walsh, Noel Doyle, Orla McGinley, Brian Glavin, Martin Jones, Edward Marnane, W. P. Univ Coll Cork Dept Elect & Elect Engn Cork Ireland Natl Univ Ireland Engn Coll & Informat Galway Ireland

ISBN: (纸本)9781424441242

This paper describes the performance of beat detection and heart rate variability (HRV) feature extraction on electrocardiogram signals which have been compressed and reconstructed with a lossy compression algorithm. The set partitioning in hierarchical trees (SPIHT) compression algorithm was used with sixteen compression ratios (CR) between 2 and 50 over the records of the MIT/BIH arrhythmia database. Sensitivities and specificities between 99% and 85% were computed for each CR utilised. The extracted HRV features were between 99% and 82% similar to the features extracted from the annotated records. A notable accuracy drop over all features extracted was noted beyond a CR of 30, with falls of 10% accuracy beyond this compression ratio.

关键词： HRV feature extraction MIT-BIH arrhythmia database QRS feature extraction SPIHT compression algorithm beat detection compression ratio data compression electrocardiogram signals electrocardiography feature extraction heart rate variability lossy ECG compression effects lossy compression algorithm medical signal processing set partitioning in hierarchical trees

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