Finite-Time Stability of Continuous Autonomous Systems
SIAM Journal on Control and Optimization
Finite Time Stability and Robust Control Synthesis of Uncertain Switched Systems
SIAM Journal on Control and Optimization
M-matrices and global convergence of discontinuous neural networks: Research Articles
International Journal of Circuit Theory and Applications
Global stability for cellular neural networks with time delay
IEEE Transactions on Neural Networks
An analysis of global asymptotic stability of delayed cellular neural networks
IEEE Transactions on Neural Networks
Absolute exponential stability of a class of continuous-time recurrent neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Solving linear programming problems with neural networks: a comparative study
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
Hi-index | 0.00 |
In this paper, we consider a general class of neural networks, which have arbitrary constant delays in the neuron interconnections, and neuron activations belonging to the set of discontinuous monotone increasing and (possibly) unbounded functions. Based on the topological degree theory and Lyapunov functional method, we provide some new sufficient conditions for the global exponential stability and global convergence in finite time of these delayed neural networks. Under these conditions the uniqueness of initial value problem (IVP) is proved. The exponential convergence rate can be quantitatively estimated on the basis of the parameters defining the neural network. These conditions are easily testable and independent of the delay. In the end some remarks and examples are discussed to compare the present results with the existing ones.