An additive diagonal-stability condition for absolute exponential stability of a general class of neural networks

IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications

Volumn 48, Issue 11, 2001, Pages 1308-1317

  Liang, Xue Bin ^a,b   Wang, Jun ^a,c  

^a IEEE   (United States)

^b UNIVERSITY OF DELAWARE   (United States)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Absolute exponential stability; Additive diagonal stability; Diagonal semistability; Global exponential stability; H matrix; Neural networks; Partial Lipschitz continuity

Indexed keywords

ABSOLUTE EXPONENTIAL STABILITY; ADDITIVE DIAGONAL-STABILITY CONDITION; DIAGONAL SEMISTABILITY; GLOBAL EXPONENTIAL STABILITY; PARTIAL LIPSCHITZ CONTINUITY;

ASYMPTOTIC STABILITY; COMPUTER SIMULATION; DIFFERENTIAL EQUATIONS; MATRIX ALGEBRA; OPTIMIZATION; THEOREM PROVING;

NEURAL NETWORKS;

EID: 0035508696     PISSN: 10577122     EISSN: None     Source Type: Journal    
DOI: 10.1109/81.964419     Document Type: Article

References (34)

1. Necessary and sufficient condition for absolute stability of neural networks
2. A simple proof of a necessary and sufficient condition for absolute stability of symmetric neural networks
3. On absolute stability of neural networks
4. On a class of globally stable neural circuits
5. Comments on 'Necessary and sufficient condition for absolute stability of neural networks
6. A comment on 'Comments on necessary and sufficient condition for absolute stability of neural networks'
7. A proof of Kaszkurewicz and Bhaya's conjecture on absolute stability of neural networks in two-neuron case
8. Absolute stability of nonsymmetric neural networks
9. A comment on 'comments on necessary and sufficient condition for absolute stability of neural networks
10. New sufficient conditions for absolute stability of neural networks
11. Absolute exponential stability of neural networks with a general class of activation functions
12. Necessary and sufficient condition for absolute exponential stability of Hopfield-type neural networks
13. Necessary and sufficient condition for absolute exponential stability of a class of nonsymmetric neural networks
14. On the analysis of global and absolute stability of nonlinear continuous neural networks
15. New conditions for global stability of neural networks with application to linear and quadratic programming problems
16. Comments on 'new conditions for global stability of neural networks with application to linear and quadratic programming problems
17. Exponential stability and a systematic synthesis of a neural network for quadratic minimization
18. Neural network for quadratic optimization with bound constraints
19. Global exponential stability of a class of neural circuits
20. Neurons with graded response have collective computational properties like those of two-state neurons
21. Cellular neural networks: Theory
22. Some generalizations of positive definiteness and monotonicity
23. Some theorems on properties of dc equations of nonlinear networks
24. Recent directions in matrix stability
25. A note on neural networks with multiple equilibrium points
26. On the application of degree theory to the analysis of resistive nonlinear networks
27. On the basic theorem of complementarity