期刊
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
卷 53, 期 2, 页码 557-589出版社
SPRINGER
DOI: 10.1007/s10589-012-9476-9
关键词
Gauss-Newton method; Penalized nonlinear least squares; Proximity operator; Lipschitz conditions with L average
An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions. Convergence results of local type are obtained, as well as an estimate of the radius of the convergence ball. Some applications for solving constrained nonlinear equations are discussed and the numerical performance of the method is assessed on some significant test problems.
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