Simulation results based on ideal mathematical model and industrial model show that the PID Elman network is prior to the modified Elman network in identification of nonlinear dynamic systems.
无论是理想的数学模型还是实际工业模型，计算机仿真结果均证明，将P ID型网络用于动态系统辨识具有更好的逼近效果。
The neural network, which is a nonlinear dynamic system, has been successfully applied in the channel equalization of binary digital communication systems.
神经网络是一种非线性动力学系统，在二进制系统信道均衡实现方面得到非常成功的应用。
The results show that this algorithm can model input and output learning kernel of dynamic nonlinear system quickly, which is superior to other learning methods of wavelet network.
结果表明该算法能够对动态非线性系统的输入输出快速学习和建模，优于其它小波网络的学习算法。
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