A new version of augmented self-scaling BFGS method
عنوان مقاله: A new version of augmented self-scaling BFGS method
شناسه ملی مقاله: JR_JMMO-11-2_007
منتشر شده در در سال 1402
شناسه ملی مقاله: JR_JMMO-11-2_007
منتشر شده در در سال 1402
مشخصات نویسندگان مقاله:
Mohamad Jourak - Department of Mathematics, Payame Noor University, P.O. Box. ۱۹۳۹۵-۳۶۹۷, Tehran, Iran
Saeed Nezhadhosein - Department of Mathematics, Payame Noor University, P.O. Box. ۱۹۳۹۵-۳۶۹۷, Tehran, Iran
Farzad Rahpeymaii - Department of Mathematics, Technical and Vocational University (TVU), Tehran, Iran
خلاصه مقاله:
Mohamad Jourak - Department of Mathematics, Payame Noor University, P.O. Box. ۱۹۳۹۵-۳۶۹۷, Tehran, Iran
Saeed Nezhadhosein - Department of Mathematics, Payame Noor University, P.O. Box. ۱۹۳۹۵-۳۶۹۷, Tehran, Iran
Farzad Rahpeymaii - Department of Mathematics, Technical and Vocational University (TVU), Tehran, Iran
A new version of the augmented self-scaling memoryless BFGS quasi-Newton update, proposed in [Appl. Numer. Math. ۱۶۷, ۱۸۷--۲۰۱, (۲۰۲۱)], is suggested for unconstrained optimization problems. To use the corresponding scaled parameter, the clustering of the eigenvalues of the approximate Hessian matrix about one point is applied with three approaches. The first and second approaches are based on the trace and the determinant of the matrix. The third approach is based on minimizing the measure function. The sufficient descent property is guaranteed for uniformly convex functions, and the global convergence of the proposed algorithm is proved both for the uniformly convex and general nonlinear objective functions, separately. Numerical experiments on a set of test functions of the CUTEr collection show that the proposed method is robust. In addition, the proposed algorithm is effectively applied to the salt and pepper noise elimination problem.
کلمات کلیدی: Unconstrained optimization, augmented BFGS, noise elimination problem
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1995555/