讨论了BP 小波神经网络在训练过程中减小误差函数时最优方向的确定和自适应调整学习率的方法。

首先论证了小波神经网络的数学基础,然后讨论了BP 小波神经网络的学习过程,重点讨论了减小误差函数最优方

向的确定方法,即如何保证步长方向与负梯度方向一致,由此得出了自适应调整学习率的简便方法。该方法具有

普遍性,有广泛的应用价值。仿真结果表明,采用最优梯度下降方向可以大幅度提高BP 小波神经网络的学习速

度。-Discussed BP wavelet neural network in the training process of reducing the error function to determine the optimal direction and adaptive learning rate adjustment method. First of all, demonstrated that the wavelet neural network mathematical basis, and then discussed the BP wavelet neural network learning process focused on reducing the error function to determine the optimal direction of approach, namely how to ensure that the direction of step with the negative gradient direction, which may out the adaptive learning rate adjustment easy way. The method is universal, has a wide range of application value. Simulation results show that the optimal direction of gradient descent can dramatically improve BP wavelet neural network learning speed.