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机译:H_∞混合延迟静态神经网络的状态估计
School of Mathematics and Statistics Shandong Normal University Ji'nan 250014 People's Republic of China;
School of Mathematics and Statistics Shandong Normal University Ji'nan 250014 People's Republic of China;
School of Mathematics and Statistics Shandong Normal University Ji'nan 250014 People's Republic of China Center for Control and Engineering Computation Shandong Normal University Ji'nan 250014 People's Republic of China;
Static neural networks; H_∞ state estimation; Leakage time-varying delay; Distributed delay; Linear matrix inequality;
机译:延迟静态神经网络的非脆弱H_∞性能状态估计的进一步改进结果
机译:对延迟静态神经网络的非脆弱H_∞性能状态估计的进一步提高结果
机译:时滞静态神经网络的$ H_ {infty} $状态估计的新结果
机译:用次级延迟分区方法对混合时间延迟的T-S模糊神经网络状态估计
机译:结合人工神经网络时滞模型的静态交通分配模型
机译:具有混合时变时滞和随机发生的控制器增益波动的Markov跳神经网络的非脆弱混合H∞和被动同步
机译:具有时滞的混合时滞模糊细胞神经网络的渐近状态估计:样本数据方法