Neural Network as a Tool for Solving Nonsmooth Optimization Problems

عنوان به زبان ديگر

پديدآورندگان

Hosseini Alireza hosseini.alireza@ut.ac.ir School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran

تعداد صفحه

4

كليدواژه

neurodynamic optimization , convergence , recurrent neural network , analog circuit

سال انتشار

1397

عنوان كنفرانس

چهارمين كنفرانس بين المللي آناليز غير خطي و بهينه سازي

زبان مدرك

انگليسي

چكيده فارسي

A neural network model for solving a class of nonsmooth optimization problems is proposed. The state trajectory of the corresponding recurrent neural network will converges globally to optimal set of the problem. In the structure of the proposed model there is not any penalty parameter.

چكيده لاتين

A neural network model for solving a class of nonsmooth optimization problems is proposed. The state trajectory of the corresponding recurrent neural network will converges globally to optimal set of the problem. In the structure of the proposed model there is not any penalty parameter.

كشور

ايران