Title :
Research on state differential artificial neural network
Author :
Ziyin Wang ; Mandan Liu ; Yicheng Cheng
Author_Institution :
Key Lab. of Adv. Control & Optimization for Chem. Processes, East China Univ. of Sci. & Technol., Shanghai, China
Abstract :
In this paper, an emerging artificial neural network is proposed and researched. The differential of exciting intensity of each neuron is mutually feedback to each other in the network. Hence the overall network turns out to be a high-order nonlinear system. Besides, the iterative equations are derived by discretizing the state equations. In this way, the network´s operating efficiency is remarkably improved. This artificial neural network is designed for fitting and predicting dynamic data, and has successfully worked in simulation part of this paper.
Keywords :
data handling; iterative methods; neural nets; data fitting; data prediction; high-order nonlinear system; iterative equation; neuron intensity; state differential artificial neural network; state equation; Artificial neural networks; Differential equations; Equations; Fitting; Mathematical model; Neurons; Real-time systems;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-6248-1
DOI :
10.1109/ICICIP.2013.6568098
