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分塊的有序范德蒙矩陣作為壓縮感知測量矩陣的研究

趙瑞珍,  王若乾,  張鳳珍,  岑翼剛,  胡紹海

趙瑞珍, 王若乾, 張鳳珍, 岑翼剛, 胡紹海. 分塊的有序范德蒙矩陣作為壓縮感知測量矩陣的研究[J]. 電子與信息學報, 2015, 37(6): 1317-1322. doi: 10.11999/JEIT140860
引用本文: 趙瑞珍, 王若乾, 張鳳珍, 岑翼剛, 胡紹海. 分塊的有序范德蒙矩陣作為壓縮感知測量矩陣的研究[J]. 電子與信息學報, 2015, 37(6): 1317-1322. doi: 10.11999/JEIT140860
Zhao Rui-zhen, Wang Ruo-qian, Zhang Feng-zhen, Cen Yi-gang, Hu Shao-hai. Research on the Blocked Ordered Vandermonde Matrix Used as Measurement Matrix for Compressed Sensing[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1317-1322. doi: 10.11999/JEIT140860
Citation: Zhao Rui-zhen, Wang Ruo-qian, Zhang Feng-zhen, Cen Yi-gang, Hu Shao-hai. Research on the Blocked Ordered Vandermonde Matrix Used as Measurement Matrix for Compressed Sensing[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1317-1322. doi: 10.11999/JEIT140860

分塊的有序范德蒙矩陣作為壓縮感知測量矩陣的研究

doi: 10.11999/JEIT140860
基金項目: 

國家自然科學基金(61073079)，中央高?；究蒲袠I(yè)務(wù)費專項基金(2013JBZ003)，高等學校博士點基金(20120009110008)和教育部新世紀優(yōu)秀人才支持計劃(NCET-12-0768)資助課題

Research on the Blocked Ordered Vandermonde Matrix Used as Measurement Matrix for Compressed Sensing

  • 摘要: 測量矩陣是壓縮感知(Compressed Sensing, CS)的重要組成部分，確定性的測量矩陣易于硬件實現(xiàn)，但是重構(gòu)信號的精度一般不如隨機矩陣。針對這一缺點，該文提出并構(gòu)造了一種新的確定性測量矩陣，稱作分塊的有序范德蒙矩陣。范德蒙矩陣具有線性不相關(guān)的性質(zhì)，在此基礎(chǔ)上加上分塊操作和對元素進行有序排列得到的分塊的有序范德蒙矩陣，實現(xiàn)了時域中的非均勻采樣，特別適合于維數(shù)較大的自然圖像信號。仿真實驗表明，對于圖像信號該矩陣具有遠高于高斯矩陣的重構(gòu)精度，可以作為實際中的測量矩陣使用。
    Abstract: The measurement matrix is an important part of Compressed Sensing (CS). Although the deterministic matrix is easy to implement by the hardware, it performs not so well as a random matrix in the signal reconstruction. To solve this problem, a new deterministic measurement matrix which is called as the blocked ordered Vandermonde matrix is proposed. The blocked ordered Vandermonde matrix is constructed on the basis of the Vandermonde matrix, whose the vectors are linearly independent. Then the block operation is taken and its elements are sorted. The proposed new measurement matrix realizes the non-uniform sampling in the time domain and is specifically suitable for the natural images whose the dimension is usually high. The simulation results show that the proposed matrix is much superior to the Gaussian matrix in the image construction, and can be used in practice.
    • HTML全文
  • Candes E J, Romberg J, and Tao T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information[J]. IEEE Transactions on Information Theory, 2006, 52(2): 489-509.
    Donoho D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.
    Donoho D L and Tsaig Y. Extensions of compressed sensing[J]. Signal Processing, 2006, 86(3): 533-548.
    Duarte M F, Davenport M A, Takhar D, et al.. Single-pixel imaging via compressive sampling[J]. IEEE Signal Processing Magazine, 2008, 25(2): 83-91.
    DeVore R. Deterministic constructions of compressed sensing matrices[J]. Journal of Complexity, 2007, 23(46): 918-925.
    林斌, 彭玉樓. 基于混沌序列的壓縮感知測量矩陣構(gòu)造算法[J]. 計算機工程與應(yīng)用, 2013, 49(23): 199-202.
    Lin Bin and Peng Yu-lou. Measurement matrix construction algorithm for compressed sensing based on chaos sequence[J]. Computer Engineering and Applications, 2013, 49(23): 199-202.
    Mohades M M, Mohades A, and Tadaion A. A reed-solomon code based measurement matrix with small coherence[J]. IEEE Signal Processing Letters, 2014, 21(7): 839-843.
    Liu Xin-ji and Xia Shu-tao. Constructions of quasi-cyclic measurement matrices based on array codes[C]. Proceedings of the IEEE International Symposium on Information Theory,
    Istanbul, Turkey, 2013: 479-483.
    Gan L. Block compressed sensing of natural images[C]. 15th IEEE International Conference on Digital Signal Processing, Cardiff, Wales, 2007: 403-406.
    張波, 劉郁林, 王開. 稀疏隨機矩陣有限等距性質(zhì)分析[J]. 電子與信息學報, 2014, 36(1): 169-174.
    Zhang Bo, Liu Yu-lin, and Wang Kai. Restricted isometry property analysis for sparse random matrices[J]. Journal of Electronics Information Technology, 2014, 36(1): 169-174.
    Bajwa W U, Haupt J, Raz G, et al.. Toeplitz-structured compressed sensing matrices[C]. Proceedings of the IEEE Workshop on Statistical Signal Processing (SSP), Madison, USA, 2007: 294-298.
    Zhao Rui-zhen, Li Hao, Qin Zhou, et al.. A new construction method for generalized Hadamard matrix in compressive sensing[C]. Proceedings of the 2011 Cross-Strait Conference on Information Science and Technology, Danshui, China, 2011: 309-313.
    居余馬. 線性代數(shù)[M]. 第2版, 北京: 清華大學出版社, 2002: 17-18.
    Ju Yu-ma. Linear Algebra[M]. 2nd Edition, Beijing: Tsinghua University Press, 2002: 17-18.
    Jalbin J, Hemalatha R, and Radha S. Two measurement matrix based nonuniform sampling for wireless sensor networks[C]. Proceedings of the 3rd International Conference on Computing Communication Networking Technologies (ICCCNT'2012), Coimbatore, India, 2012: 1-4.
    李珅, 馬彩文, 李艷, 等. 壓縮感知重構(gòu)算法綜述[J]. 紅外與激光工程, 2013, 42(S1): 225-232.
    Li Kun, Ma Cai-wen, Li Yan, et al.. Survey on reconstruction algorithm based on compressive sensing[J]. Infrared and Laser Engineering, 2013, 42(S1): 225-232.
    Mohimani H, Babaie-Zadeh M, and Jutten C. A fast approach for overcomplete sparse decomposition based on smoothed l0 norm[J]. IEEE Transactions on Signal Processing, 2009, 57(1): 289-301.
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出版歷程
  • 收稿日期:  2014-06-30
  • 修回日期:  2015-03-03
  • 刊出日期:  2015-06-19

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