BP神经网络自适应步长训练算法，采用最小误差法，梯度下降法，自适应调节权值,BP neural network training anaysis, is realized by using error feed back, gradient descent applied updating of synaptic weights

用BP神经网络实现模糊控制规则为T=int[(e +ec)/2]的模糊神经网络控制器。可以改变隐层节点数和学习速率。网络训练算法是变学习速率法。-BP neural network with fuzzy control rules for the T = int [(e+ Ec)/2] of the fuzzy neural network controller. Can change the hidden layer nodes and learning rate. Network tra

模糊神经网络，自己编的，解决神经网络全局收敛问题，训练速度快。-Fuzzy neural networks, own, and to resolve the issue of global convergence of neural network training speed.

神经网络是单个并行处理元素的集合，我们从生物学神经系统得到启发。在自然界，网 络功能主要由神经节决定，我们可以通过改变连接点的权重来训练神经网络完成特定的功能-A single neural network is a collection of parallel processing elements, we have been inspired by biological nervous system. In nature, the network function of a decisi