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Conference on Computing in Cardiology

作者： Ardhapurkar, Shubhada Manthalkar, Ramchandra Gajre, Suhas Int Ctr Excellence Engn & Managment Aurangabad Maharashtra India SGGS Inst Chem Technol Nanded Maharashtra India

ISBN: (纸本)9781457706110

Linear Predictive coding (LPC) is extensively used for analysis and compression of speech signal whereas the Discrete Wavelet Transform is widely preferred for electrocardiogram (ECG) compression. In this paper, we present LPC and wavelet based method to encode ECG signals. The compression algorithm has been evaluated with the MIT-BIH Arrhythmia Database, MIT-BIH compression database and University of Glasgow noisy and normal database. The performance is quantified by computing distortion measures. The percentage root mean square difference (PRD) is found to be below 8% and wavelet-based weighted PRD (WWPRD) below 0.25. The upper quartile value of Wavelet energy based diagnostic distortion (WEDD) is less than 0.3 even for noisy data. It is observed that, a combination of LPC and wavelet subband coding offers fixed compression of 84.09%. Classification before decompression is achieved with accuracy of 97%.

关键词： subband coding linear prediction compression algorithms wavelets wavelet energy discrete wavelet transform noisy data compression Voice Signal

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ECG Signal compression Using Wavelets. Preliminary Results

ECG Signal Compression Using Wavelets. Preliminary Results

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10th International Symposium on Signals, Circuits and Systems (ISSCS)

作者： Arvinti, Beatrice Nafornita, Corina Alexandru, Isar Costache, Marius Politehn Univ Dept Phys Fdn Engn Timisoara Romania Politehn Univ Commun Dept Elect & Telecommun Fac Timisoara Romania

ISBN: (纸本)9781457702013

The ECGs transmission problem becomes actual nowadays due to the tremendous progress in communications. One of the major aspects of the transmission is the source coding (compression). The wavelet theory becomes a tool frequently used in compression. The aim of this paper is a very fast compression algorithm based on wavelets. Some simulation results prove the performance of the proposed algorithm.

关键词： compression algorithms Discrete wavelet transforms ECG Electrocardiography Encoding Noise reduction Quantization Wavelet coefficients electrocardiography medical signal processing signal compression source coding source coding wavelet theory

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Efficient Trace Data compression using Statically Selected Dictionary

Efficient Trace Data Compression using Statically Selected D...

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29th IEEE VLSI Test Symposium (VTS)/Workshop on Design for Reliability and Variability (DRV)

作者： Basu, Kanad Mishra, Prabhat Univ Florida Gainesville FL 32611 USA

ISBN: (纸本)9781612846552

Post-silicon validation and debug have gained importance in recent years to track down errors that have escaped the pre-silicon phase. Limited observability of internal signals during post-silicon debug necessitates the storage of signal states in real time. Trace buffers are used to store these states. To increase the debug observation window, it is essential to compress these trace signals, so that trace data over larger number of cycles can be stored in the trace buffer while keeping its size constant. In this paper, we propose several dictionary based compression techniques for trace data compression that takes account of the fact that the difference between golden and erroneous trace data is small. Therefore, the static dictionary selected based on golden trace data can provide notably better compression performance than the dynamic dictionaries selected in the current approaches. This will also significantly reduce the hardware overhead by reducing the dictionary size. Our experimental results demonstrate that our approach can provide up to 60% better compression compared to existing approaches, while reducing the architecture overhead by 84%.

关键词： Buffer storage compression algorithms Data compression Dictionaries Error analysis Silicon System-on-a-chip data compression debug observation window dictionary based compression techniques dictionary size dynamic dictionaries hardware overhead integrated circuit testing internal signals logic testing post-silicon debug post-silicon validation pre-silicon phase signal states static dictionary statically selected dictionary system-on-chip trace buffers trace data compression trace signals

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3D object compression using enhanced stripification technique

3D object compression using enhanced stripification techniqu...

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

作者： Khairy, Fatma Mousa, Mohamed H. Nassar, Hamed Yasein, Mohamed S. Suez Canal Univ Dept Comp Sci Ismailia Egypt Port Said Univ Dept Elect & Comp Engn Port Said Egypt

ISBN: (纸本)9781457702518

3D meshes are one of the most common representations of 3D objects that have been used in graphics applications. They often require a huge amount of data for storage and/or transmission. In this paper, we present a new compression algorithm based on stripification of the geometric models that enables us to progressively visualize the 3D models during their transmission. The proposed algorithm encodes the geometry and the connectivity of the input model in an interwoven fashion. The main idea is to store 3D objects as strips files. The algorithm achieves compression ratios above 61 : 1 over ASCII encoded formats resulting in faster transmission and rendering of complex graphical objects.

关键词： 3D meshes 3D model visualization 3D object compression 3D object representation compression algorithms Geometry Joining processes Rendering (computer graphics) Solid modeling Strips Three dimensional displays complex graphical object rendering data compression data visualisation geometric model stripification graphics application interwoven fashion mesh generation rendering (computer graphics) solid modelling

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Structured Compressed Sensing: From Theory to Applications

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第9期59卷 4053-4085页

作者： Duarte, Marco F. Eldar, Yonina C. Univ Massachusetts Dept Elect & Comp Engn Amherst MA 01003 USA Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

Compressed sensing (CS) is an emerging field that has attracted considerable research interest over the past few years. Previous review articles in CS limit their scope to standard discrete-to-discrete measurement architectures using matrices of randomized nature and signal models based on standard sparsity. In recent years, CS has worked its way into several new application areas. This, in turn, necessitates a fresh look on many of the basics of CS. The random matrix measurement operator must be replaced by more structured sensing architectures that correspond to the characteristics of feasible acquisition hardware. The standard sparsity prior has to be extended to include a much richer class of signals and to encode broader data models, including continuous-time signals. In our overview, the theme is exploiting signal and measurement structure in compressive sensing. The prime focus is bridging theory and practice;that is, to pinpoint the potential of structured CS strategies to emerge from the math to the hardware. Our summary highlights new directions as well as relations to more traditional CS, with the hope of serving both as a review to practitioners wanting to join this emerging field, and as a reference for researchers that attempts to put some of the existing ideas in perspective of practical applications.

关键词： Approximation algorithms compressed sensing compression algorithms data acquisition data compression sampling methods

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Dynamic data compression in wireless networks

Dynamic data compression in wireless networks

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International Symposium on Advanced Networks and Telecommunication Systems (ANTS)

作者： Saket Chawla B. S. Manoj Department of Avionics Indian Institute of Space science and Technology Trivandrum India

Techniques for saving bandwidth are very important in bandwidth constrained wireless networks. One of the key concepts that save bandwidth is compression of data packets. While it has been employed over low bandwidth point-to-point wired or wireless links, multiuser communication networks such as WLANs and WMNs do not use packet compression. In this work, we designed and implemented the data packet compression mechanism for IEEE 802.11 networks and study its impact on the compression efficiency and throughput. We observed that with 1450Byte sized packets, a compression ratio of 57% is achieved with a throughput degradation of less than 10%. Further, we also propose a dynamic packet compression mechanism where the data packet compression is employed selectively. Results from a prototype implementation are presented.

关键词： compression algorithms Throughput Wireless networks Bandwidth Heuristic algorithms Data compression Software

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An ECG Data compression Method via Standard Deviation and ASCII Character Encoding

An ECG Data Compression Method via Standard Deviation and AS...

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International Conference on Emerging Applications of Information Technology (EAIT)

作者： S.K. Mukhopadhyay M. Mitra S. Mitra Department of Applied Physics University of Calcutta Kolkata India Department of Electronics Netaji Nagar Day College University of Calcutta Kolkata India

In the present paper, a software based effective ECG data compression algorithm is proposed. The whole algorithm is written in C- platform. The algorithm is tested on various ECG data of all the 12 leads taken from PTB Diagnostic ECG Database (PTB-DB). In this compression methodology, individual standard deviation of each part of the signal is calculated at first. To achieve a strict loss less compression in regions of high standard deviation and a tolerable lossy compression in rest of the signal, two different compression algorithms have developed. It is observed that this proposed algorithm can reduce the file size significantly. The data reconstruction algorithm has also been developed using the reversed logic and it is seen that data is reconstructed preserving the significant ECG signal morphology.

关键词： Arrays Electrocardiography Encoding Data compression compression algorithms Decoding Wavelet transforms

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Combining Non-stationary Prediction, Optimization and Mixing for Data compression

Combining Non-stationary Prediction, Optimization and Mixing...

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International Conference on Data compression, Communications and Processing

作者： Christopher Mattern Fakultät für Informatik und Automatisierung Technische Universität Ilmenau Ilmenau Germany

In this paper an approach to modelling nonstationary binary sequences, i.e., predicting the probability of upcoming symbols, is presented. After studying the prediction model we evaluate its performance in two non-artificial test cases. First the model is compared to the Laplace and Krichevsky-Trofimov estimators. Secondly a statistical ensemble model for compressing Burrows-Wheeler-Transform output is worked out and evaluated. A systematic approach to the parameter optimization of an individual model and the ensemble model is stated.

关键词： Optimization Context Predictive models Numerical models compression algorithms Switches Approximation methods

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The choice of wavelet bases in electrocardiogram compression algorithm

The choice of wavelet bases in electrocardiogram compression...

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International Conference on Multimedia Technology

作者： Xiurong-Bao Physical and Electronic Information College Inner Mongolia Normal University Hohhot China

ISBN: (纸本)9781612847719

This paper is associated with the choice of wavelet bases in electrocardiogram compression. The integer-to-integer wavelet transform in the algorithm, the zero-tree coding and the adaptive arithmetic coding in electrocardiogram is used. The wavelet library is composed of nine wavelets. The MIT-BIH arrhythmia database is used to test the algorithm. The experiment results show that it can significantly reduce the signal distortion by selecting optimal wavelet bases for each segment electrocardiogram in compression algorithm.

关键词： Wavelet transforms Electrocardiography Image coding Wavelet domain compression algorithms Wavelet analysis

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Sketches characterization and compression for nomadic computing

Sketches characterization and compression for nomadic comput...

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International Conference on Computer Supported Cooperative Work in Design

作者： Nelson Baloian Ramón Cruzat Richard Ibarra Javier Bustos-Jiménez Departamento de Ciencias de la Computación Universidad de Chile Santiago Chile ORAND Santiago Chile

Nomadic computing often refers to people using computer support working anywhere, anytime and not necessarily attached to a specific location or time of the day. Mobile computing and wireless ad-hoc networks are important elements in this kind of scenarios. Nowadays it is common to see architects, engineers, geologists and/or designers working on the field and sharing ideas on a collaborative media using sketches and freehand writing. On this scenario, data overflow among the peer applications often happens, since the sketches have to be distributed among all participants in real time. This paper presents a work on characterization and compression algorithms for sketches, with and without loss of information, to be used on mobile devices, in order to reduce the data traffic. We focused our study on three parameters of the algorithms: time required characterizing and compressing the sketch, size of the resulting information and human perceived of lost information. Our results present algorithms with a compression ratio lower than 1% the size of the original image without information loosing under human perception.

关键词： Mobile handsets Performance evaluation Image coding Mobile communication Collaboration Pixel compression algorithms

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