Impulsive delayed integro-differential inequality and its application on IMNNs with discrete and distributed delays

abstract

• 2019 Elsevier B.V. Impulsive differential inequality is crucial for nonlinear impulsive differential system. In this paper, an impulsive delayed integro-differential inequality is firstly presented and studied. New impulsive inequality is given by M-matrix, proof by contradiction and recursive inequality. Then, the discrete-distributed delayed memristive neural network model is constructed and its exponential stability criteria are obtained by the novel impulsive delayed inequality. Finally, two numerical examples are given to illustrate the effectiveness of exponential stability criteria.

authors

• Huang, Tingwen

published proceedings

• NEUROCOMPUTING

author list (cited authors)

• Wang, H., Tan, J., Huang, T., & Duan, S.

citation count

• 4

complete list of authors

• Wang, Huamin||Tan, Jie||Huang, Tingwen||Duan, Shukai

publication date

• May 2019

publisher

• Elsevier  Publisher

published in

• Neurocomputing  Journal

keywords

• Discrete-distributed Delays
• Exponential Stability
• Impulsive Integro-differential Inequality
• Memristive Neural Networks

Digital Object Identifier (DOI)

• 10.1016/j.neucom.2019.03.007

start page

• 99

end page

• 106

volume

• 341

URL

• http://dx.doi.org/10.1016/j.neucom.2019.03.007

user-defined tag

• 10 Reduced Inequalities