Open AccessApplication of compressed sensing theory in the method of moments
Author(s) -
Zhe Wang,
BingZhong Wang
Publication year - 2014
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.63.120202
Subject(s) - underdetermined system , computer science , compressed sensing , matrix (chemical analysis) , method of moments (probability theory) , construct (python library) , mathematical optimization , algorithm , sparse matrix , mathematics , physics , materials science , statistics , quantum mechanics , estimator , composite material , gaussian , programming language
Matrix filling and equation solving are the most computationally-expensive steps in the method of moments (MoM). Based on the compressed sensing (CS) theory, an improved method of MoM is proposed in this paper. Through introducing sparse transform matrix, the unknown response can be expressed sparsely, so we can construct and optimally solving underdetermined equation under the framework of CS. Numerical examples show that the proposed method can reduce the matrix filling cost dramatically, and also can improve the efficiency of equation solving effectively.