中文摘要：

采用投影寻踪（projection pursuit，PP）学习网络方法建立了一种新的遥感影像分类模型。该方法结合了统计学中投影寻踪算法节点函数灵活的非参数估计特点和人工神经网络的自学习功能，具有简捷的网络结构和良好的鲁棒性能。利用苏州市TM影像进行了分类实验，将分类结果与BP神经网络和最大似然法的分类结果相比较，投影寻踪学习网络的分类精度较高，具有一定的实用性。

英文摘要：

Using projection pursuit learning network （PPLN）, a new classification for remote sensing image is proposed. The PPLN algorithm integrates the advantage of artificial neural network （ANN） with nonparametric statistical technique, projection pursuit algorithm （PP）, which is capable of providing less network neurons and good robustness. In this study, the structure and improved learning algorithm of PPLN is introduced in detail. Using the TM image of Suzhou, an experiment of classification is done and the classification precision is superior to that of BP neural network and conventional maximum-likelihood.