Abstract
Complete stability of cellular neural networks and their associated dynamical system precludes the possibility of any periodic or chaotic behavior and is an important property to establish. The authors establish complete stability of the opposite-sign cellular neural network (CNN) provided that the template values fall within the range (p-1)/2<s<p-1. The results reported extend the parameter range from previously known results.<<ETX>>
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 callMore From: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
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.
