Global robust stability of complex-valued recurrent neural networks with time-delays and uncertainties Academic Article

abstract

• This paper focuses on the existence, uniqueness and global robust stability of equilibrium point for complex-valued recurrent neural networks with multiple time-delays and under parameter uncertainties with respect to two activation functions. Two sufficient conditions for robust stability of the considered neural networks are presented and established in two new time-independent relationships between the network parameters of the neural system. Finally, three illustrative examples are given to demonstrate the theoretical results.

authors

• Huang, Tingwen

published proceedings

• INTERNATIONAL JOURNAL OF BIOMATHEMATICS

author list (cited authors)

• Zhang, W., Li, C., & Huang, T.

citation count

• 25

complete list of authors

• Zhang, Wei||Li, Chuandong||Huang, Tingwen

publication date

• March 2014

publisher

• World Scientific Publishing  Publisher

published in

• International Journal of Biomathematics  Journal

keywords

• Complex-valued Recurrent Neural Networks
• Global Asymptotical Stability
• Robust Stability

Digital Object Identifier (DOI)

• 10.1142/S1793524514500168

start page

• 1450016

end page

• 1450016

volume

• 7

issue

• 2

URL

• http://dx.doi.org/10.1142/s1793524514500168