[1]徐静,王彩云.压缩感知测量矩阵优化混合方法[J].深圳大学学报理工版,2014,31(1):58-62.[doi:10.3724/SP.J.1249.2014.01058]
 Xu Jing and Wang Caiyun.A hybrid optimization method for measurement matrix in compressed sensing[J].Journal of Shenzhen University Science and Engineering,2014,31(1):58-62.[doi:10.3724/SP.J.1249.2014.01058]
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压缩感知测量矩阵优化混合方法()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第31卷
期数:
2014年第1期
页码:
58-62
栏目:
电子与信息科学
出版日期:
2014-01-14

文章信息/Info

Title:
A hybrid optimization method for measurement matrix in compressed sensing
文章编号:
20140108
作者:
徐静1王彩云2
1)南京航空航天大学电子信息工程学院 南京210016
2)南京航空航天大学航天学院 南京210016
Author(s):
Xu Jing1 and Wang Caiyun2
1)College of Electronic and Information Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, P.R.China
2)College of Astronautics, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, P.R.China
关键词:
信息处理技术压缩感知测量矩阵混沌因子动量项梯度下降法重构图像
Keywords:
information processing technology compressed sensing(CS) measurement matrix chaos factor momentum term gradient descent algorithm reconstructed image
分类号:
TP 751
DOI:
10.3724/SP.J.1249.2014.01058
文献标志码:
A
摘要:
针对压缩感知中测量矩阵的优化问题,提出一种基于混沌因子和动量项的梯度下降法.在测量矩阵优化过程中,梯度下降法具有收敛速度慢,容易陷入局部最小的缺点. 为此,基于混沌运动的随机性和遍历性,在步长变化中引入混沌因子,避免因初始步长选择不当导致算法的不稳定且实现步长的自适应变化;同时利用动量项,避免算法陷入局部最小值,提高算法的收敛速度,优化测量矩阵性能,降低测量矩阵与稀疏矩阵互相关性.仿真结果表明,该方法收敛速度快,互相关系数的分布更加集中在零附近,且重构图像的峰值信噪比大大提高.
Abstract:
A hybrid method is proposed for optimizing the measurement matrix in compressed sensing.A significantly improved gradient descent algorithm combining chaos motion and momentum term is presented to solve the problem of slow convergence speed and local minimum of gradient descent.Based on randomness and ergodicity of chaotic motion,a chaos factor is introduced to stepsize so that the stepsize is adaptive in the iteration process.Momentum term is added to avoid falling into local minimum and improve convergence speed.The simulation results have demonstrated that the speed of optimizing matrix is fast, and more mutual coherence coefficients are distributed around zero. The peak signal to noise ratio(PSNR) of reconstructed image through compressed sensing is improved with the optimized measurement matrix.

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备注/Memo

备注/Memo:
Received:2013-09-30;Accepted:2013-12-09
Foundation:National Natural Science Foundation of China(61301211)
Corresponding author:Associate professor Wang Caiyun.E-mail: wangcaiyun@nuaa.edu.cn
Citation:Xu Jing,Wang Caiyun.A hybrid optimization method for measurement matrix in compressed sensing[J]. Journal of Shenzhen University Science and Engineering, 2014, 31(1): 58-62.(in Chinese)
基金项目:国家自然科学基金资助项目(61301211)
作者简介:徐静(1989-),女(汉族),安徽省淮北市人,南京航空航天大学硕士研究生.E-mail:xujing_ll99@163.com
引文:徐静,王彩云.压缩感知测量矩阵优化混合方法[J]. 深圳大学学报理工版,2014,31(1):58-62.
更新日期/Last Update: 2014-01-08