NUMERICAL OPTIMIZATION ALGORITHMS FOR WAVEFRONT PHASE RETRIEVAL FROM MULTIPLE MEASUREMENTS | |
Li, Ji ; Zhou, Tie | |
2017 | |
关键词 | Wavefront phaseretrieval C-Rcalculus LBFGS FOURIER-TRANSFORM SIGNAL RECOVERY RECONSTRUCTION MAGNITUDE GRADIENT |
英文摘要 | Wavefront phase retrieval from a set of intensity measurements can be formulated as an optimization problem. Two nonconvex models (MLP and its variant LS) based on maximum likelihood estimation are investigated in this paper. We derive numerical optimization algorithms for real-valued function of complex variables and apply them to solve the wavefront phase retrieval problem efficiently. Numerical simulation is given with application to three test examples. The LS model shows better numerical performance than that of the MLP model. An explanation for this is that the distribution of the eigenvalues of Hessian matrix of the LS model is more clustered than that of the MLP model. We find that the LBFGS method shows more robust performance and takes fewer calculations than other line search methods for this problem.; National Natural Science Foundation of China [61421062, 11471024]; SCI(E); ARTICLE; 4; 721-743; 11 |
语种 | 英语 |
出处 | SCI |
出版者 | INVERSE PROBLEMS AND IMAGING |
内容类型 | 其他 |
源URL | [http://hdl.handle.net/20.500.11897/471627] |
专题 | 数学科学学院 |
推荐引用方式 GB/T 7714 | Li, Ji,Zhou, Tie. NUMERICAL OPTIMIZATION ALGORITHMS FOR WAVEFRONT PHASE RETRIEVAL FROM MULTIPLE MEASUREMENTS. 2017-01-01. |
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