title: Extended dissipative analysis for neural networks with time-varying delays.
abstract: In this brief, an extended dissipativity analysis was conducted for a neural network with time-varying delays. The concept of the extended dissipativity can be used to solve for the H∞, L2-L∞, passive, and dissipative performance by adjusting the weighting matrices in a new performance index. In addition, the activation function dividing method is modified by introducing a tuning parameter. Examples are provided to show the effectiveness and less conservatism of the proposed method.
authors.forename: Tae H
authors.initials: TH
authors.lastname: Lee
authors.forename: Myeong-Jin
authors.initials: MJ
authors.lastname: Park
authors.forename: Ju H
authors.initials: JH
authors.lastname: Park
authors.forename: Oh-Min
authors.initials: OM
authors.lastname: Kwon
authors.forename: Sang-Moon
authors.initials: SM
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D013997:Time Factors