基于Ｈｏｐｆｉｅｌｄ神经网络的神经计算原理，提出了一类非线性系统的参数估计方法：首先将系统参数估计问题转化为以系统模型残差平方和为目标函数的优化计算问题，然后利用连续Ｈｏｐｆｉｅｌｄ神经网络的神经计算估计待辨识参数．数字仿真结果表明，该方法不仅算法简单，而且估计精度高． Based on the neural computation principle of Hopfield neural network, a parameter estimation method for a class of nonlinear systems is proposed. Firstly, the system parameter estimation problem is transformed into the optimization calculation problem with the objective function of the sum of residuals of the system model. Then, by using Hopfield neural network The neural calculation estimates the parameters to be identified. The numerical simulation results show that the proposed method is not only simple, but also has high estimation accuracy.