شماره ركورد كنفرانس :
4819
عنوان مقاله :
A neurodynamic model for shortest path problem
پديدآورندگان :
Shojaeifard Alireza ashojaeifard@ihu.ac.ir Department of Mathematics and Statistics, Imam Hossein Comprehensive University, Tehran, Iran. , Mansoori Amin am.ma7676@yahoo.com Department of Mathematics and Statistics, Imam Hossein Comprehensive University, Tehran, Iran. , Nakhaei Amrodi Ali kpnakhaei@ihu.ac.ir Department of Mathematics and Statistics, Imam Hossein Comprehensive University, Tehran, Iran.
كليدواژه :
Shortest path problem , recurrent neural network , linear optimization problem , Stability in the sense of Lyapunov
عنوان كنفرانس :
سومين همايش بين المللي تركيبيات، رمزنگاري و محاسبات
چكيده فارسي :
In this paper, a representation of a recurrent neural network to solve the shortest path (SP) problem is given. The motivation of the paper is to design a new effective one-layer structure recurrent neural network model for solving the SP. Moreover, we show that the proposed recurrent neural network is globally exponentially stable. Finally, the numerical examples are discussed to demonstrate the performance of our proposed approach.
