A Method for Solving Nonsmooth Pseudoconvex Optimization
محورهای موضوعی : فصلنامه ریاضی
Maryam Bala Seyed Ghasir
1
(Department of Mathematics, Payame Noor University (PNU), P.O. Box 19395-4697, Tehran, Iran)
Aghileh Heydari
2
(Department of Mathematics, Payame Noor University (PNU), P.O. Box 19395-4697, Tehran, Iran)
Mohammad Ali Badamchizadeh
3
(Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran)
کلید واژه: Optimization, Recurrent neural network, Global convergence, nonsmooth pseudoconvex,
چکیده مقاله :
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.
