中国科学院机构知识库网格系统: 检索

SEAD Counter: Self-Adaptive Counters With Different Counting Ranges 期刊论文 OAI收割
IEEE-ACM TRANSACTIONS ON NETWORKING, 2021, 页码: 17
作者: Liu, Xilai; Xu, Yan; Liu, Peng; Yang, Tong; Xu, Jiaqi

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收藏 | 浏览/下载：43/0 | 提交时间：2022/06/21

Memory management Mice Arrays Random access memory System-on-chip Hash functions Computer science Estimator sketches generic counter network measurement compression self-adaptive

Linear-FM random radar waveform compressed by dechirping method 期刊论文 OAI收割
IET RADAR SONAR AND NAVIGATION, 2019, 卷号: 13, 期号: 7, 页码: 1107-115
作者: Liu, Jiafang; Zhang, Yunhua; Dong, Xiao

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收藏 | 浏览/下载：54/0 | 提交时间：2019/08/26

radar resolution FM radar random noise radar imaging frequency modulation synthetic aperture radar radar detection jamming dechirping compression method digital radio frequency memory repeat jammer random noise waveforms random radar echo signal low-speed analogue-to-digital converter LFM waveform compression high-resolution circular synthetic aperture radar imaging experiment linear-FM random radar waveform linear frequency modulation random radar waveform

A Low Overhead In-Network Data Compressor for the Memory Hierarchy of Chip Multiprocessors 期刊论文 OAI收割
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2018, 卷号: 37, 期号: 6, 页码: 1265-1277
作者: Wang, Ying; Li, Huawei; Han, Yinhe; Li, Xiaowei

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收藏 | 浏览/下载：45/0 | 提交时间：2019/12/10

Cache chip multiprocessor (CMP) compression memory hierarchy network-on-chip (NoC)

Memory Deduplication: An Effective Approach to Improve the Memory System 期刊论文 OAI收割
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2017, 卷号: 33, 期号: 5, 页码: 1103-1120
作者: Deng, YuHui; Huang, XinYu; Song, LiangShan; Zhou, YongTao; Wang, Frank

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收藏 | 浏览/下载：208/0 | 提交时间：2019/12/12

memory deduplication address-based cache content-based cache memory compression data characteristics

High-Performance Motion Estimation for Image Sensors with Video Compression 期刊论文 OAI收割
SENSORS, 2015, 卷号: 15, 期号: 8, 页码: 20752-20778
作者: Xu, Weizhi; Yin, Shouyi; Liu, Leibo; Liu, Zhiyong; Wei, Shaojun

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收藏 | 浏览/下载：118/0 | 提交时间：2019/12/13

memory bandwidth image sensors video compression motion estimation full search inter-frame data reuse

SOPC处理器的程序压缩与解压研究 学位论文 OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院大学, 2015
作者: 涂吉

收藏 | 浏览/下载：66/0 | 提交时间：2015/09/02

星载处理机代码压缩存储系统多字典可编程片上系统 On-board Computer Code Compression Memory System Multi-Dictionary System-on-a-Programmable-Chip

SoC test data compression technique based on RLE-G (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Advanced Measurement and Test, AMT 2010, May 15, 2010 - May 16, 2010, Sanya, China
作者: Liu W.; Yang L.; Yang L.; Zheng X.

收藏 | 浏览/下载：35/0 | 提交时间：2013/03/25

Test data compression has been an effective way to reduce test data volume and test time as well as to solve automatic test equipment (ATE) memory and bandwidth limitation. We analyze the limitations of current test data compression algorithm and draw on the previous experience to deduce an optimal compression coding model suitable for SoC test data. In addition in this paper we make full use of the relevance of the test vectors and the advantages of statistical coding to present an efficient test data compression method RLE-G based on the coding model and give the RLE-G the optimal compression efficiency of the boundary conditions and realization steps. The experimental results for ISCAS 89 benchmark circuits demonstrate RLE-G have the excellent advantages of high compression ratio. (2010) Trans Tech Publications.

基于共享存储和Gzip的并行压缩算法研究 期刊论文 OAI收割
计算机工程与设计, 2009, 卷号: 30, 期号: 4, 页码: 781-784
宋刚; 蒋孟奇; 张云泉; 刘胜飞

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收藏 | 浏览/下载：21/0 | 提交时间：2010/08/24

共享存储并行编程数据压缩 OpenMP Gzip OpenMP Gzip shared memory parallel programming data compression OpenMP gzip

Compression of remote sensing image based on Listless Zerotree Coding and DPCM (EI CONFERENCE) 会议论文 OAI收割
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Chen S.-L.; Huang L.-Q.

收藏 | 浏览/下载：33/0 | 提交时间：2013/03/25

The data quantity of remote sensing image is very large. Furthermore the lowest frequency subband contains the main energy of original image and reflects the coarse of original image after remote sensing image is transformed by wavelet so it is very important to the reconstructed image. Therefore a hybrid image compression method based on Listless Zerotree Coding (LZC) and DPCM is presented namely the lowest frequency subband is compressed by DPCM and others are compressed by LZC. LZC is a kind of zerotree coding algorithm for hardware implementation which is based on SPIHT and substitutes two significant bit maps for three lists in SPIHT algorithm. Thereby LZC significantly reduces the memory requirement and complexity during encoding and decoding procedure. But LZC doesn't recognize the significance of grandchild sets so the PSNR values of LZC are lower than SPIHT's and the compression speed drops. It is improved by adding a significant bit map that recognizes the significance of grandchild sets. A comparison reveals that the PSNR results of the hybrid compression method are 2 dB higher than those of LZC and the compression speed is also improved.

The compression and storage method of the same kind of medical images-DPCM (EI CONFERENCE) 会议论文 OAI收割
4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China
作者: Liu H.; Liu H.; Liu H.

收藏 | 浏览/下载：16/0 | 提交时间：2013/03/25

Medical imaging has started to take advantage of digital technology opening the way for advanced medical imaging and teleradiology. Medical images however require large amounts of memory. At over 1 million bytes per image a typical hospital needs a staggering amount of memory storage (over one trillion bytes per year) and transmitting an image over a network (even the promised superhighway) could take minutes - too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. Several compression techniques with different compression ratio have been developed. However the lossless techniques which allow for perfect reconstruction of the original images yield modest compression ratio while the techniques that yield higher compression ratio are lossy that is the original image is reconstructed only approximately Medical imaging poses the great challenge of having compression algorithms that are lossless (for diagnostic and legal reasons) and yet have high compression ratio for reduced storage and transmission time. To meet this challenge we are developing and studying some compression schemes which are either strictly lossless or diagnostically lossless taking advantage of the peculiarities of medical images and of the medical practice. In order to increase the Signal to-Noise Ratio (SNR) by exploitation of correlations within the source signal a method of combining differential pulse code modulation (DPCM) is presented.