This paper deals with the issue of mixed H∞ and L2 − L∞ anti-synchronization control for chaotic delayed recurrent neural networks with unknown parameters and stochastic noise. By means of the LyapunovKrasovskii functional method and some stochastic analysis techniques, an adaptive controller strategy is proposed to guarantee the mixed H∞ and L2 −L∞ anti-synchronization of the drive and response systems. When there is no stochastic noise, it is shown that the present control strategy is less conservative and less complex than a previously reported adaptive control method. Finally, a numerical example is employed to illustrate the applicability of the proposed adaptive control strategy.
This paper deals with the issue of mixed H∞ and L2 − L∞ anti-synchronization control for chaotic delayed recurrent neural networks with unknown parameters and stochastic noise. By means of the LyapunovKrasovskii functional method and some stochastic analysis techniques, an adaptive controller strategy is proposed to guarantee the mixed H∞ and L2 −L∞ anti-synchronization of the drive and response systems. When there is no stochastic noise, it is shown that the present control strategy is less conservative and less complex than a previously reported adaptive control method. Finally, a numerical example is employed to illustrate the applicability of the proposed adaptive control strategy.