Abstract

Robust Exponential stability of continuous-time attractor neural networks with delays is discussed. A new sufficient condition ensuring existence and uniqueness of periodic solution for a general class of interval dynamical systems are obtained. Discrete-time analogue of the continuous-time systems with periodic input is formulated and we study their dynamical characteristics. The robust exponential stability and periodicity of the continuous-time systems is preserved by the discrete-time analogue without any restriction imposed on the uniform discretization step-size.

Full Text
Paper version not known

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 call

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.