Motivated by the study of regularization for sparse problems,we propose a new regularization method for sparse vector recovery.We derive sufficient conditions on the well-posedness of the new regularization,and design...Motivated by the study of regularization for sparse problems,we propose a new regularization method for sparse vector recovery.We derive sufficient conditions on the well-posedness of the new regularization,and design an iterative algorithm,namely the iteratively reweighted algorithm(IR-algorithm),for efficiently computing the sparse solutions to the proposed regularization model.The convergence of the IR-algorithm and the setting of the regularization parameters are analyzed at length.Finally,we present numerical examples to illustrate the features of the new regularization and algorithm.展开更多
The formation of nonequilibrium phase by mechanical alloying (MA) of Fe and B powders in a high energy vibration ball mill has been made for Fe100-xBx system with x=15. 30, 35, 45,55 and 70. By using the X-ray diffrac...The formation of nonequilibrium phase by mechanical alloying (MA) of Fe and B powders in a high energy vibration ball mill has been made for Fe100-xBx system with x=15. 30, 35, 45,55 and 70. By using the X-ray diffraction, magnetic measurement and M6ssbauer spectrummethods, it was revealed that the structure of the MA product varies with milling time and B contents.展开更多
In this paper,we propose a fast proximity point algorithm and apply it to total variation(TV)based image restoration.The novel method is derived from the idea of establishing a general proximity point operator framewo...In this paper,we propose a fast proximity point algorithm and apply it to total variation(TV)based image restoration.The novel method is derived from the idea of establishing a general proximity point operator framework based on which new first-order schemes for total variation(TV)based image restoration have been proposed.Many current algorithms for TV-based image restoration,such as Chambolle’s projection algorithm,the split Bregman algorithm,the Berm´udez-Moreno algorithm,the Jia-Zhao denoising algorithm,and the fixed point algorithm,can be viewed as special cases of the new first-order schemes.Moreover,the convergence of the new algorithm has been analyzed at length.Finally,we make comparisons with the split Bregman algorithm which is one of the best algorithms for solving TV-based image restoration at present.Numerical experiments illustrate the efficiency of the proposed algorithms.展开更多
基金Project supported by the National Natural Science Foundation of China(No.61603322)the Research Foundation of Education Bureau of Hunan Province of China(No.16C1542)
文摘Motivated by the study of regularization for sparse problems,we propose a new regularization method for sparse vector recovery.We derive sufficient conditions on the well-posedness of the new regularization,and design an iterative algorithm,namely the iteratively reweighted algorithm(IR-algorithm),for efficiently computing the sparse solutions to the proposed regularization model.The convergence of the IR-algorithm and the setting of the regularization parameters are analyzed at length.Finally,we present numerical examples to illustrate the features of the new regularization and algorithm.
文摘The formation of nonequilibrium phase by mechanical alloying (MA) of Fe and B powders in a high energy vibration ball mill has been made for Fe100-xBx system with x=15. 30, 35, 45,55 and 70. By using the X-ray diffraction, magnetic measurement and M6ssbauer spectrummethods, it was revealed that the structure of the MA product varies with milling time and B contents.
基金the National Science Foundation of China under grants(No.61271014)Specialized Research Fund for the Doctoral Program of Higher Education(20124301110003)the Graduated Students Innovation Fund of Hunan Province(CX2012B238).
文摘In this paper,we propose a fast proximity point algorithm and apply it to total variation(TV)based image restoration.The novel method is derived from the idea of establishing a general proximity point operator framework based on which new first-order schemes for total variation(TV)based image restoration have been proposed.Many current algorithms for TV-based image restoration,such as Chambolle’s projection algorithm,the split Bregman algorithm,the Berm´udez-Moreno algorithm,the Jia-Zhao denoising algorithm,and the fixed point algorithm,can be viewed as special cases of the new first-order schemes.Moreover,the convergence of the new algorithm has been analyzed at length.Finally,we make comparisons with the split Bregman algorithm which is one of the best algorithms for solving TV-based image restoration at present.Numerical experiments illustrate the efficiency of the proposed algorithms.
