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检索条件"主题词=compression algorithms"

共 2082 条记录，以下是401-410 订阅

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Research on Sinusoidal compression Algorithm for Power Signal Based on Four-Parameter Sine Fitting

Research on Sinusoidal Compression Algorithm for Power Signa...

引用

International Conference on Information Science and Control Engineering (ICISCE)

作者： Guangfu Liu Xue Dong Coll. of Inf. & Control Eng. China University of Petroleum Beijing Changping-qu Beijing CN

ISBN: (纸本)9781509025367

Power signal implies useful messages to discover working status of submersible motors, but it should be compressed efficiently before transmitted because of the huge data. Based on the approximate sinusoidal characteristic of power signal, sinusoidal compression algorithm is proposed which references four-parameter sine fitting algorithm and static Huffman compression algorithm. For power signal with sampling frequency of 10kHz, the compression ratio can be as high as 2.5 by Sinusoidal compression algorithm, while only 1.5 by normal static Huffman algorithm. Simulation signal is generated based on real power signal, and slot harmonics are also concluded which are related with the motor speed. Simulation results implied that the compression ratio by sinusoidal compression algorithm is better than that of the static Huffman or other common power signal compression methods.

关键词： Fitting compression algorithms Underwater vehicles Encoding Harmonic analysis Predictive models Curve fitting

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A new hybrid data compression algorithm for weather radar

A new hybrid data compression algorithm for weather radar

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Ke Ma Chongyang Li Haozheng Li Xi'an Electronic Engineering Research Institute Xi'an China

ISBN: (纸本)9781509047444

The existent problem of the weather radar data lies in its too large data which is not conducive to its storage and transmission. This paper put forward a hybrid compression algorithm of the weather radar data that consists of three steps including pre-compression, lossy compression and lossless compression. Firstly, the paper introduced the radar data's types and characteristics, analyzing the pre-compression algorithm; Secondly, according to the practical requirements of the diverse users, it proposed the adoption of lossless compression and lossy compression algorithm for the data; Finally, the flow chart of mixed compression algorithm was presented and verified based on the actual data.

关键词： Meteorology Meteorological radar compression algorithms Algorithm design and analysis Data compression Doppler radar

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A Comparison of Road-Network-Constrained Trajectory compression Methods

A Comparison of Road-Network-Constrained Trajectory Compress...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Yudian Ji Hao Liu Xiaoying Liu Ye Ding Wuman Luo The Hong Kong University of Science and Technology University of Macau

ISBN: (纸本)9781509053827

The popularity of location-acquisition devices has led to a rapid increase in the amount of trajectory data collected. The large volume of trajectory data causes the difficulties of storing and processing the data. Various trajectory compression methods are therefore proposed to deal with these problems. In this paper, we overview the existing road-network-constrained trajectory compression methods and propose a novel classification based on the features leveraged by them. We also propose new methods that fill in the research blanks indicated by the classification. We conduct a thorough comparison among the existing and new road-network-constrained trajectory compression methods. The performances of the methods are studied via various metrics on real-world dataset. We make new discoveries regarding the performances and the scalability of existing methods, and provide guidelines of road-network-constrained trajectory compression for various scenarios.

关键词： Trajectory Roads Encoding compression algorithms Scalability Routing Presses

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Topological ordering based iterative TCAM rule compression using bi-partite graphs

Topological ordering based iterative TCAM rule compression u...

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International Conference on Network Protocols

作者： Rui Li Wenjie Li Bruhadeshwar Bezawada Zheng Qin College of Information Science and Engineering Hunan University Changsha China Mahindra Ecole Centrale Hyderabad India

ISBN: (纸本)9781509032822

For fast packet classification, the de-facto industry standard is to use Ternary Content Addressable Memory (TCAM) chips where each chip stores one classifier rule and a given packet is checked against all such rules in parallel. In spite of the TCAM advantages, for a large number of rules, the TCAM deployment becomes expensive and the power consumption increases significantly. Therefore, it is desirable to reduce the number of TCAM rules while retaining the original classification semantics. In this work, we present efficient graph-based algorithms and data structures that allow us to capture the rule ordering relationships and iteratively compress the TCAM rules. Through extensive experiments, we show that our algorithm achieves 75% reduction of firewall rule sets on an average and even achieves an additional 24% compression on the output rule set of the state-of-the-art solutions.

关键词： Sorting Semantics Redundancy compression algorithms Publishing Algorithm design and analysis Conferences

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A low complexity edge-preserved image compression algorithm for LCD overdrive

A low complexity edge-preserved image compression algorithm ...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Chao-Yang Chang Chung-Hsun Huang Hui-Fu Chen Chingwei Yeh Yuan-Sun Chu Tay-Jyi Lin National Chung Cheng University Minhsiung TW

ISBN: (纸本)9781509023349

Overdrive technique is mandatory for liquid crystal display (LCD) to mitigate the motion blur phenomenon. As the display resolution increases, the image data should be highly compressed to reduce the usages of frame memory and bandwidth. Since current high quality compression algorithms inevitably require large embedded memory (line buffer) and complex computations, a low complexity line-buffer-free edge-preserved compression algorithm is proposed in this paper to reserve the edge information for overdrive technique of LCD. Performance evaluations show that the proposed edge-preserved compression achieves above 20% PSNR improvements as compared to the conventional DPCM compression up to 6:1 compression ratio.

关键词： Image coding Image edge detection Liquid crystal displays Pulse modulation Image segmentation compression algorithms Memory management

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Efficient Dictionary compression for Processing RDF Big Data Using Google BigQuery

Efficient Dictionary Compression for Processing RDF Big Data...

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IEEE Global Communications Conference

作者： Omer Dawelbeit Rachel McCrindle School of Systems Engineering University of Reading

ISBN: (纸本)9781509013296

The Resource Description Framework (RDF) data model, is used on the Web to express billions of structured statements in a wide range of topics, including government, publications, life sciences, etc. Consequently, processing and storing this data requires the provision of high specification systems, both in terms of storage and computational capabilities. On the other hand, cloud-based big data services such as Google BigQuery can be used to store and query this data without any upfront investment. Google BigQuery pricing is based on the size of the data being stored or queried, but given that RDF statements contain long Uniform Resource Identifiers (URIs), the cost of query and storage of RDF big data can increase rapidly. In this paper we present and evaluate a novel and efficient dictionary compression algorithm which is faster, generates small dictionaries that can fit in memory and results in better compression rate when compared with other large scale RDF dictionary compression. Consequently, our algorithm also reduces the BigQuery storage and query cost.

关键词： Resource Description Framework refuse derived fuel Dictionaries as Topic big data compression ratio dimensional data Google compression algorithms data services webs World Wide Web congenital web

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Fast lossy compression algorithm for medical images

Fast lossy compression algorithm for medical images

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International Conference on Electronics and Information Technology (EIT)

作者： A. Sadchenko O. Kushnirenko O. Plachinda Department of Electronic Telecommunication Systems Odessa National Polytechnic University Odessa Ukraine Department of Petroleum and Chemical Engineering Odessa National Polytechnic University Odessa Ukraine

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： Image coding Algorithm design and analysis Medical diagnostic imaging compression algorithms Transforms Image restoration

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Low-latency lossless compression using dual-stream coding

Low-latency lossless compression using dual-stream coding

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International Symposium on Information Theory and Its Applications, ISITA

作者： Haruhiko Kaneko Yuki Katsu School of Computing Tokyo Institute of Technology Tokyo Graduate School of Information Sci. & Eng. Tokyo Institute of Technology Tokyo

Lossless compression in data-bus systems and storage devices will be effective to improve the performance of data intensive computings which require high-throughput data transfers between components, e.g., processing nodes, memory modules, and storage devices. For such applications, the latency and throughput of codec will be important factors as well as the compression ratio. This paper proposes a low-latency high-throughput compression algorithm suitable for hardware implementation. The algorithm has two coding streams, namely, differential-word and parameter-word codings, which can be executed in parallel. A naive codec is designed using Verilog-HDL, and implementation results show that the complexity and throughput are comparable to conventional low-latency compression algorithms. The compression ratio is evaluated by computer simulation, and the results show that the proposed algorithm has superior compression ratios compared to the conventional algorithm.

关键词： Encoding Delays compression algorithms Buffer storage Dictionaries Zirconium Hardware

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Wearable EEG via lossless compression

Wearable EEG via lossless compression

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Guillermo Dufort Federico Favaro Federico Lecumberry Álvaro Martín Juan P. Oliver Julián Oreggioni Ignacio Ramírez Gadiel Seroussi Leonardo Steinfeld Facultad de Ingeniería Universidad de la República Montevideo Uruguay

This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176μW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.

关键词： Electroencephalography Random access memory compression algorithms Power demand Microcontrollers Prediction algorithms Correlation

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Clockwise compression for trajectory data under road network constraints

Clockwise compression for trajectory data under road network...

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IEEE International Conference on Big Data

作者： Yudian Ji Yuda Zang Wuman Luo Xibo Zhou Ye Ding Lionel M. Ni Hong Kong University of Science and Technology Tsinghua University University of Macau

ISBN: (纸本)9781467390064

Big trajectory data introduces severe challenges for data storage and communication. In this paper, we propose a novel compression framework called Clockwise compression Framework (CCF) for big trajectory data compression under road network constraints. In CCF, we design several new methods: 1) a spatial compression algorithm called Enhanced Clockwise Encoding (ECE), 2) a temporal compression algorithm called Fitting-based Temporal Simplification (FTS), and 3) a dedicated querier that processes queries based on the above spatial and temporal compression algorithms, without fully decompressing the trajectroy data. By leveraging the topological information of the road network, CCF is able to perform both spatial compression and temporal compression in on-line modes. We perform extensive experiments in a real big trajectory dataset to verify both effectiveness and efficiency of our methods. CCF shows promising performances in various metrics and outperforms the state-of-the-art methods.

关键词： Roads Trajectory Encoding Presses compression algorithms Data compression Performance evaluation

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