Robust stability analysis for BAM neural networks of neutral type with time-varying delays and linear fractional uncertainties
- Yunxi Zhang, Jia Liu, Yongxin Li
- Corresponding Author
- Yunxi Zhang
Available Online December 2015.
- https://doi.org/10.2991/icmmcce-15.2015.86How to use a DOI?
- Bidirectional associative memory neural networks; Robust stability; Time-varying delays; Linear fractional form; Lyapunov-Krasovskii functional
- This paper investigates the problem of robust stability for bidirectional associative memory (BAM) neural networks of neutral type with time-varying delays and linear fractional uncertainties. By employing integral equality and constructing a new Lyapunov-Krasovskii functional, a sufficient criterion is proposed on robust asymptotic stability for a given BAM neural networks with linear fractional uncertainties. The parameters uncertainties are expressed in a linear fractional form, which includes the norm bounded uncertainties as a special case. Numerical examples are provided to illustrate the effectiveness and less conservatism of the main result.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yunxi Zhang AU - Jia Liu AU - Yongxin Li PY - 2015/12 DA - 2015/12 TI - Robust stability analysis for BAM neural networks of neutral type with time-varying delays and linear fractional uncertainties BT - 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering PB - Atlantis Press UR - https://doi.org/10.2991/icmmcce-15.2015.86 DO - https://doi.org/10.2991/icmmcce-15.2015.86 ID - Zhang2015/12 ER -