参数不确定量子细胞神经网络与Lorenz超混沌系统的函数投影同步研究

研究了具有不确定参数的量子细胞神经网络系统与Lorenz超混沌系统的函数投影同步.设计了自适应追踪控制器来实现两个不同系统渐进同步到已知的比例函数,并运用Lyapunov稳定性方法进行了证明.理论分析了量子细胞神经网络系统不确定参数的系数向量线性无关性,实现了不确定参数的识别和估计.数值仿真结果验证了函数投影同步和参数估计的有效性.

Function projective synchronization of quantum cellular neural network and Lorenz hyperchaotic system with uncertain parameters

In the paper, function projective synchronization of quantum cellular neural network with uncertain system parameters and Lorenz hyperchaotic system is studied. The adaptive controllers are proposed to make the states of two different chaotic systems asymptotically synchronized up to a desired scaling function. We also present the relevant proof by applying Lyapunov stability theory. Moreover, linear independence of coefficient vector of uncertain system parameters in quantum cellular neural network is analyzed theoretically, which aims to realize the unknown parameter identification and estimation. Numerical simulations are made to show the effectiveness of the function projective synchronization and parameter estimation.