دانشگاه آزاد اسلامی واحد علوم و تحقیقات

 آمار

تعداد نشریات50
تعداد شماره‌ها2,232
تعداد مقالات20,476
تعداد مشاهده مقاله25,267,753
تعداد دریافت فایل اصل مقاله22,921,805
Ghomashi, A., Abbasi, M.. (1397). A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems. , 10(4), 339-347.
A. Ghomashi; M. Abbasi. "A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems". , 10, 4, 1397, 339-347.
Ghomashi, A., Abbasi, M.. (1397). 'A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems', , 10(4), pp. 339-347.
Ghomashi, A., Abbasi, M.. A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems. , 1397; 10(4): 339-347.

A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems

International Journal of Industrial Mathematics
مقاله 3، دوره 10، شماره 4، بهمن 2018، صفحه 339-347  XML اصل مقاله (435.36 K)
نوع مقاله: Research Paper
نویسندگان
A. Ghomashi email orcid ؛ M. Abbasi
Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, ‎Iran.
چکیده
In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global convergence of the proposed neural network is proved.
کلیدواژه‌ها
Dynamical system؛ Strictly convex quadratic programming؛ Stability؛ Global convergence؛ Recurrent neural network
آمار
تعداد مشاهده مقاله: 372
تعداد دریافت فایل اصل مقاله: 479


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب