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中文摘要：
给出了一种用于变形预测的基于扩展Kalman滤波的神经网络学习算法，与BP算法相比，该方法具有更好的收敛率和学习能力．实例计算表明，该方法具有较高的精度和较快的计算速度．
英文摘要：
A new learning algorithm for a multilayered neural network based on extended Kalman filter is proposed to predict the deformation of structure. The EKF learning algorithm is better than the BP algorithm as convergence is improved and can provide much more accuracy learning results. Experiments in forecasting the deformation of structure prove that the proposed algorithm has much more accuracy and faster speed.
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