Matrix Analysis For Scientists And Engineers
Matrix Analysis For Scientists And Engineers
Global Robust Exponential Stability of Interval General BAM Neural Network with Delays
Neural Processing Letters
Neural Processing Letters
Improved global robust asymptotic stability criteria for delayed cellular neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Global exponential stability of competitive neural networks with different time scales
IEEE Transactions on Neural Networks
Global Exponential Stability of Multitime Scale Competitive Neural Networks With Nonsmooth Functions
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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We prove local uniform stability for a class of parametric uncertain competitive multi-time scale neural networks and determine the conditions under which stability holds as simple relationships between the neural parameters. It is assumed that the resulting parametric perturbations are only limited by their bounds. The stability conditions are established based on Gershgorin's Theorem and at the same time a more realistic upper bound is obtained than with the conservative method for the fast time scale associated with the neural activity state.