Abstract
A model of structure dynamic neural network, which simulates the learning skills such as human beings and animals, is proposed in this paper. This model contains two main steps: 1) the structure learning phase possesses the ability of online generation and ensures the number of the neural nodes of the neural network; 2) the parameter learning phase adjusts the interconnection weights of neural network to achieve favourable approximation performance. The structure learning algorithm consists of growing and pruning methods, and then, the Lyapunov stability theory is used to analyse the stability of this new algorithm. Finally, this new dynamic neural network is used to track the non-linear functions; simulation results show that this new algorithm can achieve favourable performance.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Modelling, Identification and Control
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
