On the basis of the theories mentioned above , we put neural network and kalman filter all together . we have the neural network learning algorithm based on the extended kalman filter . in order to compare traditional bp and ekf learning algorithms , we use single - strap prediction and multi - strap prediction method and apply this algorithm in stock price forecast of pufayinhang ( code : 600000 ) , handan - gangtie ( code : 600001 ) and guiguandianli ( code : 6000236 ) 我们将此算法应用到股票价格预测中，分别运用单步预测和多步预测两种方法，以浦发银行( 600000 ) 、邯郸钢铁( 600001 )和桂冠电力( 600236 )三支股票的价格为对象进行实证，分析比较基于扩展kalman滤波的神经网络学习算法及其改进算法与bp算法的优劣。
