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检索条件"主题词=Compression algorithms"

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A novel approach of data compression for dynamic data

A novel approach of data compression for dynamic data

引用

IEEE International Conference on System of Systems Engineering (SoSE)

作者： Rahul Gupta Ashutosh Gupta Suneeta Agarwal Department of Computer Science and Engineering Motilal Nehru National Institute of Technology Allahabad India Department of Computer Science and Engineering IERT Allahabad India

This paper presents a compression algorithm for dynamic data, the size of which keeps on increasing frequently. It is an efficient data compression technique comprising of a block approach that keeps the data in compressed form as long as possible and enables the data to be appended to the already compressed text. The approach requires only a minimal decompression for supporting update of data. The algorithm reduces the unnecessary time spent in compression-decompression approaches for dynamic documents deigned till now to a minimum. Further, the text document can be modified as required without decompressing and again compressing the whole document.

关键词： Data compression Computer science Data engineering compression algorithms Dictionaries Algorithm design and analysis Databases Information retrieval Office automation Data structures

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Real-time image compression using SIMD architectures

Real-time image compression using SIMD architectures

引用

Computer Architectures for Machine Perception (CAMP)

作者： P. Moravie H. Essafi C. Lambert-Nebout J.-L. Basille Commissariat à I'Energie Atomique L.E.T.I. Gif-sur-Yvette France Centre Spatial de Toulouse Toulouse France ENSEEIHT Toulouse France

Today, in the digitized satellite image domain, the need for high-dimension images is increasing considerably. To transmit or to store such images (more than 6000/spl times/6000 pixels), we need to reduce their data volume, and so we have to use image compression techniques. In most cases, these operations have to be processed in real time. The large amount of computations required by classical image compression algorithms prohibits the use of common sequential processors. To solve this problem, CEA (in collaboration with CNES) has tried to define the best-suited architecture for image compression. In order to achieve this aim, we developed and evaluated a new parallel image compression algorithm for general-purpose parallel computers using data-parallelism. This paper presents this new parallel image compression algorithm. We present implementation results on several parallel computers. We also examine load balancing and data mapping problems. We end by defining optimal characteristics of the parallel machine for real-time image compression.

关键词： Image coding Discrete wavelet transforms Continuous wavelet transforms Algorithm design and analysis Concurrent computing Wavelet transforms Fourier transforms Computer architecture compression algorithms Parallel machines

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Wavelet based ECG compression algorithm for emergency mobile telemedicine

Wavelet based ECG compression algorithm for emergency mobile...

引用

SICE Annual Conference

作者： Sun K. Yoo B.s. Kim Department of Medical Engineering Center for Emergency Medical Informatics Yonsei University College of Medicine Seoul South Korea Human Identification Research Center Center of Signal Processing Research South Korea

In this paper, we propose a wavelet-based ECG compression algorithm for emergency mobile telemedicine over cellular network. The proposed algorithm can achieve a low delay, while maintaining reconstructed signal quality by employing waveform partitioning, adaptive frame size adjustment, wavelet compression, flexible bit allocation, and header compression. The performances of the proposed algorithm in terms of reconstructed signal quality, processing delay, and error resilience were evaluated over CDMA 1x EVDO network deployed widely in Korea

关键词： Electrocardiography compression algorithms Telemedicine Partitioning algorithms Land mobile radio cellular systems Propagation delay Bit rate Performance evaluation Signal processing Resilience

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Pyramid vector coding for high quality audio compression

Pyramid vector coding for high quality audio compression

引用

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

作者： D. Cadel G. Parladori Cefriel Milan Italy Alcatel Telecom Vimercate Italy

The target of this work is the high quality audio coding at low bit rate. It is shown how pyramid vector coding (PVC) can conveniently replace the classical Huffman coding technique in audio compression systems, providing also an advantage in the bit allocation procedure. The compression performances can be further improved by fixing an upper limit value to the vector components.

关键词： Audio compression Entropy coding Bit rate Huffman coding Statistics Vector quantization Equations Telecommunications Audio coding compression algorithms

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Fast lossless compression of scientific floating-point data

Fast lossless compression of scientific floating-point data

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Data compression Conference (DCC)

作者： P. Ratanaworabhan Jian Ke M. Burtscher Computer Systems Laboratory Cornell University Ithaca NY USA

In scientific computing environments, large amounts of floating-point data often need to be transferred between computers as well as to and from storage devices. compression can reduce the number of bits that need to be transferred and stored. However, the run-time overhead due to compression may be undesirable in high-performance settings where short communication latencies and high bandwidths are essential. This paper describes and evaluates a new compression algorithm that is tailored to such environments. It typically compresses numeric floating-point values better and faster than other algorithms do. On our data sets, it achieves compression ratios between 1.2 and 4.2 as well as compression and decompression throughputs between 2.8 and 5.9 million 64-bit double-precision numbers per second on a 3 GHz Pentium 4 machine.

关键词： compression algorithms Delay Bandwidth Concurrent computing Computational modeling Analytical models Computer simulation Libraries Registers Data engineering

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Adaptive lossless forward move dictionary based compression

Adaptive lossless forward move dictionary based compression

引用

International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Deepa Raj Seema Gupta BabaSaheb Bhimrao Ambedkar University Lucknow INDIA

ISBN: (纸本)9781479968329

For storing and transmitting data from one end to another, size of the data should be reduced in size for better bandwidth and increase speed of device. Online compression is in great demand as more and more of the work is on online platform. Numerous static compression methods are there but they are time consuming and require complete data before compression. It requires two pass compressions but online compression take one pass compression for encoding and decoding simultaneously. A dictionary based compression technique can be applied to reduce the data size for better bandwidth utilization and hence faster transmission of data. In this paper we generate dictionary of incoming data according to first come first serve basis. Initially first block of some size is compressed using adaptive tree method and simultaneously dictionary is generated during processing and a particular code of 9 bits is provided for each string generated with LZW method and forward move basis method. The efficiency will be enhanced if repetition of string is greater in the document. We use a median to store coming data during transmission of previous data after compression. This way we create a block of data of particular size and apply compression on the block.

关键词： Dictionaries Image coding Vegetation Adaptation models Receivers Bandwidth compression algorithms

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A Low Power 16-bit RISC with Lossless compression Accelerator for Body Sensor Network System

A Low Power 16-bit RISC with Lossless Compression Accelerato...

引用

IEEE Asian Conference on Solid-State Circuits (ASSCC)

作者： Hyejung Kim Sungdae Choi Hoi-Jun Yoo Department of Electrical Engineering and Computer Science Semiconductor System Laboratory KAIST Daejeon South Korea

A low power 16-bit RISC is proposed for body sensor network system. The proposed IPEEP scheme provides zero overhead for the wakeup operation. The lossless compression accelerator is embedded in the RISC to support the low energy data compression. The accelerator consists of 16times16-bit storage array which has vertical and horizontal access path. By using the accelerator the energy consumption of the lossless compression operation is reduced by 93.8%. The RISC is implemented by 1-poly 6-metal 0.18 um CMOS technology with 16 k gates. It operates at 4 MHz and consumes 24.2 uW at 0.6 V supply voltage.

关键词： Reduced instruction set computing Body sensor networks Base stations Energy consumption Registers Data compression Sensor systems CMOS technology compression algorithms Wireless sensor networks

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An information theoretic model for adaptive lossy compression

An information theoretic model for adaptive lossy compressio...

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： R. Zamir K. Rose Department Electrical Engineering Systems Tel-Aviv University Tel-Aviv Israel Department of ECE University of California Santa Barbara CA USA

We investigate the underlying mechanism of universal sequential, fixed distortion, lossy source coding algorithms, through the "eyes" of a random code. We model the adaptive codebook as a "mixed type" random code whose codeword type distribution evolves with time while its dimension goes to infinity. The evolution law in our model has a structure of a tree; a type inherits its frequency in the code from its parent-types matching probabilities. We find that this mechanism naturally selects the "good" codeword types for compressing the (unknown) source. As a consequence, the code becomes optimal for the source, and approaches the rate-distortion function as the time, and hence the dimension, go to infinity. Beyond its analytical interest, this model also provides guidelines for developing lossy string matching (Lempel-Ziv-like) algorithms.

关键词： H infinity control Frequency Algorithm design and analysis compression algorithms Source coding Pressing Rate-distortion Speech analysis Guidelines Speech coding

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GPU-accelerated adaptive compression framework for genomics data

GPU-accelerated adaptive compression framework for genomics ...

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IEEE International Conference on Big Data

作者： GuiXin Guo Shuang Qiu ZhiQiang Ye BingQiang Wang Lin Fang Mian Lu Simon See Rui Mao BGI-Shenzhen Shenzhen P.R. China A *STAR Institute of HPC Singapore BGI-NVIDIA Joint Innovation Lab Shenzhen P.R. China Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen University Shenzhen P.R. China

Genomics data is being produced at an unprecedented rate, especially in the context of clinical applications and grand challenge questions. There are various types of data in genomics research, most of which are stored as plain text tables. A data compression framework tailored to this file type is introduced in this paper, featuring a combination of generic compression algorithms, GPU acceleration, and column-major storage. This approach is the first to achieve both compression and decompression rates of around 100MB/s on commodity hardware without compromising compression ratio. By selecting appropriate compression schemes for each column of data, this framework efficiently exploits data redundancy while remaining applicable to a wide range of formats. The GPU-accelerated implementation also properly exploits the parallelism of compression algorithms. Finally, this paper presents a novel first-order Markov model based transformation, with evidence that it is at least as effective as Burrows-Wheeler and Move-To-Front in some contexts.

关键词： Graphics processing units Bioinformatics Genomics Markov processes Transforms compression algorithms Acceleration

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A Novel Dictionary Management Scheme of LZW compression Algorithm Based on Insignificant Dictionary Area

A Novel Dictionary Management Scheme of LZW Compression Algo...

引用

IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Xiaoyong Cheng Bing Li Jiaxin Wu Wenhui Li Chao Luo Jiayi Su School of Microelectronics Southeast University School of Cyber Science and Engineering Southeast University School of Software Engineering Southeast University Southeast University Shenzhen Research Institute China

ISBN: (纸本)9781665446006

In order to avoid the possible degradation of the compression ratio, the dictionary management scheme is employed when the dictionary of Lempel-Ziv-Welch (LZW) algorithm is filled. Dictionary reset (DR) and least recently used (LRU) are two dictionary management schemes widely used. However, DR trades compression ratio for less time overhead and LRU obtains a high compression ratio while time and memory are sacrificed. This paper proposes a novel insignificant dictionary area LZW (IDA-LZW) which has a high and stable compression ratio while maintaining acceptable compression time and excellent decompression time. The proposed dictionary management scheme called IDA consists of dictionary partition and impact factor (IF) which returns the dictionary area should be cleared for new entries. Three variants of IDA-LZW and LZW with DR and LRU are implemented and show that the proposed scheme achieves the best average compression while consuming reasonable resources. Furthermore, comparisons are made with the results in the paper recently published to prove the proposed scheme is valuable.

关键词： Degradation Dictionaries Image coding Conferences Memory management compression algorithms

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