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Computers in Cardiology (CinC)

作者： R. Bedini D. Franchi G.L. Generali S. Severi IFC CNR PISA University Of Pisa Italy Esaote Spa Firenze

To solve some problems of data storage and transmission related to the systems for automatic interpretation of the electrocardiogram (ECG) various classes of reversible and irreversible compression algorithms have been tested on the database produced by CSE. Errors of the reconstructed signal have been evaluated by means of PRD, RMS and other synthetic parameters together with the visual analysis by a cardiologist. Tracing rebuilt from the compressed signal has been analyzed using the MEANS program of automatic interpretation, and diagnostic answers with the related measurements have been compared with the results obtained on the original signal. Inconsistent issues have been reexamined by a cardiologist to determine the artifacts and the type and amount of information lost because of compression. The results define the limits of the different classes of compression methods in relation to the accuracy expected in the diagnosis.< >

关键词： Data compression Testing Electrocardiography compression algorithms Signal analysis Cardiology Filters Data communication RF signals Frequency

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NEW ASYMPTOTIC BOUNDS AND IMPROVEMENTS ON THE LEMPEL-ZIV DATA-compression ALGORITHM

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IEEE TRANSACTIONS ON INFORMATION THEORY 1991年第3期37卷 721-729页

作者： BENDER, PE WOLF, JK Center for Magnetic Recording Research University of California San Diego La Jolla CA USA

Recently, there has been an interest in increasing the capacity of storage systems through the use of information lossless data compression. Several algorithms are being investigated and implemented. One such algorithm is the Lempel-Ziv data compression algorithm. A new data compression algorithm is presented based on the original Lempel-Ziv algorithm and bounds are derived showing the improved Lempel-Ziv algorithm's performance as compared to the original Lempel-Ziv algorithm's performance. In addition, both algorithms are implemented in software and are compared with each other as well as with the Lempel-Ziv-Welch data compression algorithm.

关键词： compression ratio compression algorithms completeness Lempel-Ziv algorithms Bound Data compression software implementation Lempel-Ziv algorithm asymptotic

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THEORETICAL AND EXPERIMENTAL RATE DISTORTION PERFORMANCE IN compression OF AMBULATORY ECGS

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 1991年第3期38卷 260-266页

作者： HAMILTON, PS TOMPKINS, WJ UNIV WISCONSIN DEPT ELECT ENGN MADISON WI 53706 USA

We compare ECG data compression algorithms based on signal entropy for a given mean-square-error (MSE) compression distortion. By defining the distortion in terms of the MSE and assuming the ECG signal to be a Gaussian process we are able to estimate theoretical rate distortion bounds from average ECG power spectra. These rate distortion bounds give estimates of the minimum bits per second (bps) required for storage of ECG data with a given MSE regardless of compression method. From average power spectra of the MIT/BIH arrhythmia database we have estimated rate distortion bounds for ambulatory ECG data, both before and after average beat subtraction. These rate distortion estimates indicate that, regardless of distortion, average beat subtraction reduces the theoretical minimum data rate required for ECG storage by approximately 100 bits per second (bps). Our estimates also indicate that practical ambulatory recording requires a compression distortion on the order of 11-mu-V rms. We have compared the performance of common ECG compression algorithms on data from the MIT/BIH database. We sampled and quantized the data to give distortion levels of 2, 5, 8, 11, and 14-mu-V rms. These results indicate that, when sample rates and quantization levels are chosen for optimal rate distortion performance, minimum data rates can be achieved by average beat subtraction followed by first differencing of the residual signal. Achievable data rates approximate our theoretical estimates at low distortion levels and are within 60 bps at higher distortion levels.

关键词： Rate-distortion Electrocardiography Databases compression algorithms Data compression Entropy Estimation theory Monitoring Solid state circuits Linear predictive coding

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compression OF THE AMBULATORY ECG BY AVERAGE BEAT SUBTRACTION AND RESIDUAL DIFFERENCING

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 1991年第3期38卷 253-259页

作者： HAMILTON, PS TOMPKINS, WJ UNIV WISCONSIN DEPT ELECT ENGNMADISONWI 53706

We implemented a method for compression of the abulatory ECG that includes average beat subtraction and first differencing of residual data. Our previous investigations indicated that this method is superior to other compression methods with respect to data rate as a function mean-squared-error distortion. Based on previous results we selected a sample rate of 100 samples per second and a quantization step size of 35-mu-V. These selections allow storage of 24 h of two-channel ECG data in 4 Mbytes of memory with a minimum rms distortion. For this sample rate and quantization level, we show that estimation of beat location and quantizer location can significantly affect compression performance. Improved compression resulted when beats were located with a temporal resolution of 5 ms and coarse quantization was performed in the compression loop. For the 24-h MIT/BIH arrhythmia database our compression algorithm coded a single-channel of ECG data with an average data rate of 174 bits per second.

关键词： Electrocardiography Databases compression algorithms Quantization Data compression Predictive coding Real time systems Computational efficiency Prediction algorithms Huffman coding

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FIXED DATA-BASE VERSION OF THE LEMPEL-ZIV DATA-compression ALGORITHM

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IEEE TRANSACTIONS ON INFORMATION THEORY 1991年第3期37卷 878-890页

作者： WYNER, AD ZIV, J TECHNION ISRAEL INST TECHNOL FAC ELECT ENGNIL-32000 HAIFAISRAEL

It is demonstrated that a variant of the Lempel-Ziv data compression algorithm where the data base is held fixed and is reused to encode successive strings of incoming input symbols is optimal, provided that the sourc... 详细信息

关键词： Data compression Decoding Entropy Encoding compression algorithms Databases Binary sequences Statistics

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ADAPTIVE compression CODING

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IEEE TRANSACTIONS ON COMMUNICATIONS 1991年第8期39卷 1245-1254页

作者： NASIOPOULOS, P WARD, RK MORSE, DJ UNIV BRITISH COLUMBIA DEPT ELECT ENGNVANCOUVER V6T 1W5BCCANADA

A compression technique which preserves edges in compressed pictures is developed. It is desirable to build edge preservation characteristics in compression methods since many applications in engineering and vision depend on edge information. In this paper we present a compression algorithm which adapts itself to the local nature of the image. Smooth regions are represented by their averages and edges are preserved using quad trees. Textured regions are encoded using BTC (block truncation coding) and a modification of BTC using look-up tables. We developed the latter (BTC with look-up tables) so as 1) to improve on the compression ratio of BTC and 2) to leave the visual quality of compression exactly the same as that of BTC. A threshold using a range which is the difference between the maximum and the minimum grey levels in a 4 x 4 pixel quadrant is used. At the recommended value of the threshold (equal to 18), the quality of the compressed textured regions is very high, the same as that of AMBTC (absolute moment block truncation coding) but the edge preservation quality is far superior to that of AMBTC. This significant improvement is achieved at compression levels (1.1-1.2 b/pixel) which are better than that of AMBTC (1.63). compression levels below (0.5-0.8) b/pixel may be achieved. The high quality of edge preservation of this method does not change at these low compression levels or as the threshold value changes. However, a postfilter is needed to improve the blocky appearance in the smooth and textured regions.

关键词： Image coding Image edge detection Quantization Biomedical engineering Military aircraft compression algorithms Helium Aerospace engineering Robot vision systems Aircraft propulsion

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Unbalanced tree-growing algorithms for practical image compression

Unbalanced tree-growing algorithms for practical image compr...

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

作者： K.L. Oehler E.A. Riskin R.M. Gray Information Systems Laboratory University of Stanford Stanford CA USA Department of Electrical Engineering University of Washington Seattle WA USA

A vector quantization compression system is presented which is suitable for use in commercial applications, i.e., efficient enough to encode a wide variety of images and simple enough to decode the images in real time using software (for machine compatibility). A fixed-rate code with unbalanced tree structure is used, and a method of unbalanced tree growing is extended. Simple prediction techniques are applied to improve coded image quality.< >

关键词： Image coding Decoding Color Vector quantization Image quality Table lookup compression algorithms Algorithm design and analysis Information systems Laboratories

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Image compression using integrated lossless/lossy methods

Image compression using integrated lossless/lossy methods

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

作者： M.A. Bassiouni A.P. Tzannes M.C. Tzannes N.S. Tzannes Department of Computer Science University of Central Florida Orlando USA ROME Air Development Center USA Electrical Engineering & Computer Science Department University of California Berkeley USA Electrical Engineering Department University of Central Florida Orlando USA

A new compression scheme is described that aims at improving the fidelity of reconstructed images through the parallel application of both lossless and lossy compression techniques. The purpose of the scheme is to obtain compression ratios higher than those obtained by lossless compression schemes and at the same time produce reconstructed images with better fidelity than those normally obtained with lossy techniques. Tests so far have shown that the integrated lossless/lossy (IL/L) compression scheme consistently improves the fidelity of reconstructed images compared to well-known image compression algorithms. Specifically, the new scheme gives better fidelity (20% to 55% reduction in mean square error) than the DCT algorithm under equal compression ratios.< >

关键词： Image coding Pixel Discrete cosine transforms Image reconstruction Decoding compression algorithms Concatenated codes Gray-scale Image resolution Discrete transforms

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Improved structures based on neural networks for image compression

Improved structures based on neural networks for image compr...

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IEEE Workshop on Neural Networks for Signal Processing

作者： S. Carrato G. Ramponi A. Premoli G.L. Sicuranza DEEI University of Trieste Trieste Italy

The problem of efficient image compression through neural networks (NNs) is addressed. Some theoretical results on the application of 2-layer linear NNs to this problem are given. Two more elaborate structures, based on a set of NNs, are further presented; they are shown to be very efficient while remaining computationally rather simple.< >

关键词： Neural networks Image coding Image reconstruction Backpropagation algorithms Karhunen-Loeve transforms Mean square error methods compression algorithms Vectors Joining processes

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An Overview of the MPEG/audio compression Algorithm

An Overview of the MPEG/audio Compression Algorithm

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IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

作者： D. Pan Digital Equipment Corporation Maynard MA USA

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