title: Global convergence rate of recurrently connected neural networks.
abstract: We discuss recurrently connected neural networks, investigating their global exponential stability (GES). Some sufficient conditions for a class of recurrent neural networks belonging to GES are given. Sharp convergence rate is given too.
authors.affiliation: Laboratory of Nonlinear Mathematics Science, Institute of Mathematics, Fudan University, Shanghai, China. tchen@fudan.edu.cn
authors.forename: Tianping
authors.initials: T
authors.lastname: Chen
authors.forename: Wenlian
authors.initials: W
authors.lastname: Lu
authors.forename: Shun-ichi
authors.initials: S
authors.lastname: Amari