A novel complex varying‐parameter finite‐time zeroing neural network (VPFTZNN) for finding a solution to the time‐dependent division problem is introduced. A comparative study in relation to the zeroing neural network (ZNN) and finite‐time zeroing neural network (FTZNN) is established in terms of the error function and the convergence speed. The error graphs of the VPFTZNN design show promising results and perform better than corresponding ZNN and FTZNN graphs. The proposed dynamical systems are suitable tools for overcoming the division by zero difficulty, which appears in the time‐varying division. An application of the introduced VPFTZNN model in an output tracking control time‐varying linear system is demonstrated.

中文翻译：

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时变除法的改进有限时归零神经网络

介绍了一种新颖的复杂的变参数有限时间归零神经网络（VPFTZNN），用于寻找时间依赖的除法问题的解决方案。根据误差函数和收敛速度，建立了与调零神经网络（ZNN）和有限时间调零神经网络（FTZNN）相关的比较研究。VPFTZNN设计的误差图显示出令人满意的结果，并且比相应的ZNN和FTZNN图表现更好。所提出的动力学系统是克服零难度除法的合适工具，该方法出现在时变除法中。演示了引入的VPFTZNN模型在输出跟踪控制时变线性系统中的应用。