Abstract
Abstract In this paper we report the result of a Monte Carlo study on the probability of chaos in large dynamical systems. We use neural networks as the basis functions for the system dynamics and choose parameter values for the networks randomly. Our results show that as the dimension of the system and the complexity of the network increase, the probability of chaotic dynamics increases to 100%. Since neural networks are dense in the set of dynamical systems, our conclusion is that most large systems are chaotic.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
