Global robust stability of interval delayed neural networks

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Global robust stability of interval delayed neural networks

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In recent years, the problem of global robust stability of Hopfield-type interval delayed neural networks has received considerable attention. A number of criteria for the global robust stability of such networks have been reported in the literature. On the basis of the idea of dividing (in respect of both the connection weight matrix A and the delayed connection weight matrix B) the given interval into two intervals, four new criteria for the global robust stability of such networks are established. The criteria are in the form of linear matrix inequality and, hence, computationally tractable. The criteria yield a less conservative condition compared with many recently reported criteria, as is demonstrated with an example.

Inspec keywords: stability; linear matrix inequalities; delays; Hopfield neural nets

Other keywords: global robust stability; linear matrix inequality; delayed connection weight matrix; connection weight matrix; Hopfield-type interval delayed neural networks

Subjects: Algebra; Neural nets (theory)

References

    1. 1)
      • V. Singh . Global robust stability of delayed neural networks: estimating upper limit of norm of delayed connection weight matrix. Chaos, Solitons Fractals , 1 , 259 - 263
    2. 2)
      • V. Singh . Improved global robust stability for interval-delayed Hopfield neural networks. Neural Process. Lett. , 3 , 257 - 265
    3. 3)
    4. 4)
      • V. Singh . Improved global robust stability criterion for delayed neural networks. Chaos, Solitons Fractals , 1 , 224 - 229
    5. 5)
    6. 6)
    7. 7)
      • S. Boyd , L.E. Ghaoui , E. Feron , V. Balakrishnan . (1994) Linear matrix inequalities in system and control theory.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
      • P. Gahinet , A. Nemirosky , A.J. Laub , M. Chilali . (1995) LMI control toolbox – for use with matlab.
    13. 13)
    14. 14)
    15. 15)
    16. 16)
    17. 17)
    18. 18)
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