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A Method for Solving Nonsmooth Pseudoconvex Optimization | ||
International Journal of Mathematical Modelling & Computations | ||
مقاله 2، دوره 12، 1 (WINTER) - شماره پیاپی 45، خرداد 2022، صفحه 15-25 اصل مقاله (266.08 K) | ||
نوع مقاله: Full Length Article | ||
شناسه دیجیتال (DOI): 10.30495/ijm2c.2022.1938594.1230 | ||
نویسندگان | ||
Maryam Bala Seyed Ghasir* 1؛ Aghileh Heydari1؛ Mohammad Ali Badamchizadeh2 | ||
1Department of Mathematics, Payame Noor University (PNU), P.O. Box 19395-4697, Tehran, Iran | ||
2Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran | ||
چکیده | ||
In this paper, a two layer recurrent neural network (RNN) is shown for solving nonsmooth pseudoconvex optimization . First it is proved that the equilibrium point of the proposed neural network (NN) is equivalent to the optimal solution of the orginal optimization problem. Then, it is proved that the state of the proposed neural network is stable in the sense of Lyapunov, and convergent to an exact optimal solution of the original optimization. Finally two examples are given to illustrate the effectiveness of the proposed neural network. | ||
کلیدواژهها | ||
Recurrent neural network؛ Nonsmooth pseudoconvex؛ Optimization؛ Global convergence | ||
آمار تعداد مشاهده مقاله: 265 تعداد دریافت فایل اصل مقاله: 78 |