搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

一种基于选择性测量的自适应压缩感知方法

康荣宗 田鹏武 于宏毅

引用本文:
Citation:

一种基于选择性测量的自适应压缩感知方法

康荣宗, 田鹏武, 于宏毅

An adaptive compressed sensing method based on selective measure

Kang Rong-Zong, Tian Peng-Wu, Yu Hong-Yi
PDF
导出引用
  • 针对低信噪比条件下现有压缩感知系统重构性能严重恶化的问题,提出了一种基于选择性测量的自适应压缩感知结构. 首先推导并分析了经过压缩测量的噪声的统计特性及其对重构性能的影响;然后基于输出能量最小化准则,设计了一种压缩域投影滤波联合噪声检测的自适应感知器,感知获得噪声子空间的位置信息;进一步利用该信息构造选择性压缩测量矩阵,智能选择测量信号,同时“屏蔽”噪声分量,极大提高了压缩测量值的信噪比. 仿真结果表明,相对于现有压缩感知结构,选择性测量的压缩感知结构明显改善了含噪稀疏信号的重构性能,可更好地应用于吸波材料的前端特性分析、认知无线电的频谱感知等领域.
    An adaptive compressed sensing architecture based on selective measure is proposed in this paper, in order to reduce the effects of non-sparse noise component on the performance of existing compressed sensing reconstruction algorithm. Firstly, in this paper we analyze and deduces the statistics characteristic of the measured noise and its influence on the reconstruction performance; then we propose a compressive-domain projection filter combined with iterative noise detector method to obtain the location information of noise subspace based on minimal output energy criteria; thirdly, we measure matrix adaptively with the location information, and focus on the signal subspace directly without sensing the noise component in analog part. Simulation results show that compared with the existing compressed sensing procedures, our method can obviously improve the performance of reconstruction of signals with noise, and can be used to perform the front-end spectrum analysis of absorbing materials and better detect the active channels in cognitive radio.
    • 基金项目: 国家科技重大专项(批准号:2008ZX03006)资助的课题.
    • Funds: Project supported by the National Science and Technology Major Projects of China (Grant No. 2008ZX03006).
    [1]

    Sun L K, Cheng H F, Zhou Y J, Wang J 2012 Chin. Phys. B 21 055201

    [2]

    Zhou Y J, Pang Y Q, Cheng H F 2013 Chin. Phys. B 22 015201

    [3]

    Donoho D L 2006 IEEE Trans. Inform. Theory 52 1289

    [4]

    Candes E J 2006 Proceedings of the International Congress of Mathematicians Madrid, Spain, August 22-30, 2006 p1433

    [5]

    Candes E J, Romberg J, Tao T 2006 IEEE Trans. Inform. Theory 52 489

    [6]

    Zhang J C, Fu N, Qiao L Y, Peng X Y 2014 Acta Phys. Sin. 63 030701 (in Chinese) [张京超, 付宁, 乔立岩, 彭喜元 2014 物理学报 63 030701]

    [7]

    Sun B, Jiang J J 2011 Acta Phys. Sin. 60 110701 (in Chinese) [孙彪, 江建军 2011 物理学报 60 110701]

    [8]

    Donoho D L, Tsaig Y 2006 Signal Process. 86 533

    [9]

    Tibshirani R 1996 J. Roy. Stat. Soc. B 58 267

    [10]

    Figueiredo M A T, Nowak R D, Wright S J 2007 IEEE J. Sel. Top. Sig. Proc. 1 586

    [11]

    Gorodnitsky I F, Rao B D 1997 IEEE Trans. Sig. Proc. 45 600

    [12]

    Rao B D, Engan K, Cotter S F 2003 IEEE Trans. Sig. Proc. 51 760

    [13]

    Neff R, Zakhor A 1997 IEEE Trans. Circ. Syst. Vide. 7 158

    [14]

    Needell D, Vershynin R 2010 IEEE Trans. Sel. Top. Sig. Proc. 4 310

    [15]

    Donoho D L, Tsaig Y, Drori I 2012 IEEE Trans. Inform. Theory. 58 1094

    [16]

    Davenport M A, Wakin M B 2010 IEEE Trans. Inform. Theory 56 4395

    [17]

    Tropp J A, Gilbert A C 2007 IEEE Trans. Inform. Theory 53 4655

    [18]

    Varadarajan B, Khudanpur S, Trac T D 2011 IEEE Sig. Proc. Lett. 18 27

    [19]

    Haupt J, Castro R M, Nowak R 2011 IEEE Trans. Inform. Theory 57 6222

    [20]

    Davenport M A, Arias-Castro E 2012 Proceedings of the IEEE International Symposium on Information Theory Massachusetts Ave, USA, July 1-6, 2012 p1827

    [21]

    Hanneke S 2011 Ann. Stat. 39 333

    [22]

    Koltchinskii V 2010 J. Mach. Learn. Res. 11 2457

    [23]

    Laska J N, Kirolos S, Duarte M F 2007 Proceedings of the IEEE International Symposium on Circuits and Systems New Orleans, Louisiana, USA, May 27-30, 2007 p1959

    [24]

    Baraniuk R 2007 IEEE Sig. Proc. Mag. 24 118

    [25]

    Donoho D L 2006 Commun. Pur. Appl. Math. 59 797

    [26]

    Eldar Y C, Kuppinger P, Bolcskei H 2010 IEEE Trans. Sig. Proc. 58 3042

    [27]

    Daubechies I, Devore R, Fornasier M, Gunturk C S 2010 Comm. Pure Appl. Math. 63 1

  • [1]

    Sun L K, Cheng H F, Zhou Y J, Wang J 2012 Chin. Phys. B 21 055201

    [2]

    Zhou Y J, Pang Y Q, Cheng H F 2013 Chin. Phys. B 22 015201

    [3]

    Donoho D L 2006 IEEE Trans. Inform. Theory 52 1289

    [4]

    Candes E J 2006 Proceedings of the International Congress of Mathematicians Madrid, Spain, August 22-30, 2006 p1433

    [5]

    Candes E J, Romberg J, Tao T 2006 IEEE Trans. Inform. Theory 52 489

    [6]

    Zhang J C, Fu N, Qiao L Y, Peng X Y 2014 Acta Phys. Sin. 63 030701 (in Chinese) [张京超, 付宁, 乔立岩, 彭喜元 2014 物理学报 63 030701]

    [7]

    Sun B, Jiang J J 2011 Acta Phys. Sin. 60 110701 (in Chinese) [孙彪, 江建军 2011 物理学报 60 110701]

    [8]

    Donoho D L, Tsaig Y 2006 Signal Process. 86 533

    [9]

    Tibshirani R 1996 J. Roy. Stat. Soc. B 58 267

    [10]

    Figueiredo M A T, Nowak R D, Wright S J 2007 IEEE J. Sel. Top. Sig. Proc. 1 586

    [11]

    Gorodnitsky I F, Rao B D 1997 IEEE Trans. Sig. Proc. 45 600

    [12]

    Rao B D, Engan K, Cotter S F 2003 IEEE Trans. Sig. Proc. 51 760

    [13]

    Neff R, Zakhor A 1997 IEEE Trans. Circ. Syst. Vide. 7 158

    [14]

    Needell D, Vershynin R 2010 IEEE Trans. Sel. Top. Sig. Proc. 4 310

    [15]

    Donoho D L, Tsaig Y, Drori I 2012 IEEE Trans. Inform. Theory. 58 1094

    [16]

    Davenport M A, Wakin M B 2010 IEEE Trans. Inform. Theory 56 4395

    [17]

    Tropp J A, Gilbert A C 2007 IEEE Trans. Inform. Theory 53 4655

    [18]

    Varadarajan B, Khudanpur S, Trac T D 2011 IEEE Sig. Proc. Lett. 18 27

    [19]

    Haupt J, Castro R M, Nowak R 2011 IEEE Trans. Inform. Theory 57 6222

    [20]

    Davenport M A, Arias-Castro E 2012 Proceedings of the IEEE International Symposium on Information Theory Massachusetts Ave, USA, July 1-6, 2012 p1827

    [21]

    Hanneke S 2011 Ann. Stat. 39 333

    [22]

    Koltchinskii V 2010 J. Mach. Learn. Res. 11 2457

    [23]

    Laska J N, Kirolos S, Duarte M F 2007 Proceedings of the IEEE International Symposium on Circuits and Systems New Orleans, Louisiana, USA, May 27-30, 2007 p1959

    [24]

    Baraniuk R 2007 IEEE Sig. Proc. Mag. 24 118

    [25]

    Donoho D L 2006 Commun. Pur. Appl. Math. 59 797

    [26]

    Eldar Y C, Kuppinger P, Bolcskei H 2010 IEEE Trans. Sig. Proc. 58 3042

    [27]

    Daubechies I, Devore R, Fornasier M, Gunturk C S 2010 Comm. Pure Appl. Math. 63 1

  • [1] 王攀, 王仲根, 孙玉发, 聂文艳. 新型压缩感知计算模型分析三维电大目标电磁散射特性. 物理学报, 2023, 72(3): 030202. doi: 10.7498/aps.72.20221532
    [2] 陈炜, 郭媛, 敬世伟. 基于深度学习压缩感知与复合混沌系统的通用图像加密算法. 物理学报, 2020, 69(24): 240502. doi: 10.7498/aps.69.20201019
    [3] 李慧, 赵琳, 李亮. 基于贝叶斯压缩感知的周跳探测与修复方法. 物理学报, 2016, 65(24): 249101. doi: 10.7498/aps.65.249101
    [4] 时洁, 杨德森, 时胜国, 胡博, 朱中锐. 基于压缩感知的矢量阵聚焦定位方法. 物理学报, 2016, 65(2): 024302. doi: 10.7498/aps.65.024302
    [5] 庄佳衍, 陈钱, 何伟基, 冒添逸. 基于压缩感知的动态散射成像. 物理学报, 2016, 65(4): 040501. doi: 10.7498/aps.65.040501
    [6] 郭静波, 李佳文. 二进制信号的混沌压缩测量与重构. 物理学报, 2015, 64(19): 198401. doi: 10.7498/aps.64.198401
    [7] 张茜, 刘光斌, 余志勇, 郭金库. 一种面向中继协作频谱感知系统的自适应全局最优化算法. 物理学报, 2015, 64(1): 018404. doi: 10.7498/aps.64.018404
    [8] 李广明, 吕善翔. 混沌信号的压缩感知去噪. 物理学报, 2015, 64(16): 160502. doi: 10.7498/aps.64.160502
    [9] 陈明生, 王时文, 马韬, 吴先良. 基于压缩感知的目标频空电磁散射特性快速分析. 物理学报, 2014, 63(17): 170301. doi: 10.7498/aps.63.170301
    [10] 王哲, 王秉中. 压缩感知理论在矩量法中的应用. 物理学报, 2014, 63(12): 120202. doi: 10.7498/aps.63.120202
    [11] 张新鹏, 胡茑庆, 程哲, 钟华. 基于压缩感知的振动数据修复方法. 物理学报, 2014, 63(20): 200506. doi: 10.7498/aps.63.200506
    [12] 郑仕链, 杨小牛, 赵知劲. 用于随机解调器压缩采样的重构判定方法. 物理学报, 2014, 63(22): 228401. doi: 10.7498/aps.63.228401
    [13] 李龙珍, 姚旭日, 刘雪峰, 俞文凯, 翟光杰. 基于压缩感知超分辨鬼成像. 物理学报, 2014, 63(22): 224201. doi: 10.7498/aps.63.224201
    [14] 张京超, 付宁, 乔立岩, 彭喜元. 一种面向信息带宽的频谱感知方法研究. 物理学报, 2014, 63(3): 030701. doi: 10.7498/aps.63.030701
    [15] 宁方立, 何碧静, 韦娟. 基于lp范数的压缩感知图像重建算法研究. 物理学报, 2013, 62(17): 174212. doi: 10.7498/aps.62.174212
    [16] 冯丙辰, 方晟, 张立国, 李红, 童节娟, 李文茜. 基于压缩感知理论的非线性γ谱分析方法. 物理学报, 2013, 62(11): 112901. doi: 10.7498/aps.62.112901
    [17] 白旭, 李永强, 赵生妹. 基于压缩感知的差分关联成像方案研究. 物理学报, 2013, 62(4): 044209. doi: 10.7498/aps.62.044209
    [18] 郑仕链, 杨小牛. 用于认知无线电协作频谱感知的混合蛙跳算法群体初始化技术. 物理学报, 2013, 62(7): 078405. doi: 10.7498/aps.62.078405
    [19] 孙彪, 江建军. 标志位频谱感知方法研究. 物理学报, 2011, 60(11): 110701. doi: 10.7498/aps.60.110701
    [20] 郑仕链, 楼才义, 杨小牛. 基于改进混合蛙跳算法的认知无线电协作频谱感知. 物理学报, 2010, 59(5): 3611-3617. doi: 10.7498/aps.59.3611
计量
  • 文章访问数:  5188
  • PDF下载量:  545
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-01-01
  • 修回日期:  2014-06-06
  • 刊出日期:  2014-10-05

/

返回文章
返回