采用bp神经网络对其进行函数拟合。误差反向传播网络（bp网络）是目前人工神经网络模式中最具代表性，应用最广泛的一种模型，具有自学习、自组织、自适应和很强的非线性映射能力，可以以任意精度逼近任意连续函数。-The bp neural network to its function fitting. Error back propagation network (bp network) is the artificial neural network model of the most repres

解决了非线性函数的逼近问题,实现了BP神经网络在非线性函数逼近中的应用。得出了信号的频率与隐含点之间，隐含点与函数逼近能力之间的关系——隐含层神经元数目越多。-Solved the problem of nonlinear function approximation, and realized the application of the BP neural network in nonlinear function approximation. Between signal frequenc

遗传算法、粒子群算法优化BP神经网络-非线性函数拟合-Genetic algorithm and particle swarm optimization for BP neural network nonlinear function fitting