摘要
提出一种基于奇异值分解的观测矩阵(SVBT),用于实时监测灾情.在随机向量中分别挑选N个和M个连续原子进行镜像处理,构造基础托普利兹矩阵;将基础托普利兹矩阵进行奇异值分解,得到奇异值;根据奇异值和均值的关系自适应修正奇异值矩阵,从而产生SVBT矩阵.仿真结果表明,相比于其他经典矩阵,SVBT矩阵的观测性能具有较大的优越性,提高了重构质量.
A measurement matrix based on singular value decomposition(SVBT)is proposed for real-time monito-ring of disaster situation.N and M continuous atoms are chosen separately from a random vector to construct the basic toeplitz matrix;The basic toeplitz matrix is decomposed for the singular values by the use of singular value decomposition algorithm.Diagonal elements of the singular matrix is adjusted according to the relationship between the singular value and avarage value,so as to obtain the SVBT matrix.Simulation results show that the SVBT meas-urement matrix has much better performance than other traditional measurement matrices,and improves reconstruc-tion quality.
作者
许学杰
王玥颖
XU Xuejie;WANG Yueying(College of Physics and Electronic Information,Huaibei Normal University,Huaibei 235000,China)
出处
《牡丹江师范学院学报(自然科学版)》
2025年第3期15-21,共7页
Journal of Mudanjiang Normal University:Natural Sciences Edition
基金
国家自然科学基金项目(41875040)
安徽省高校自然科学研究项目(KJ2019B17)
安徽省大学生创新项目(S202310373124)
安徽省高等学校质量工程教学研究项目(2022jyxm1389)
淮师大重点教研项目(2022xjxyj025)
淮师大实验室开放项目(2023syskf006)
淮师大质量工程教学研究项目(2021xjxyj025)。
关键词
压缩感知
观测矩阵
奇异值分解
重构质量
compressed sensing
measurement matrix
singular value decomposition
reconstruction quality
