Adaptive learning rate CNN for SAR ATR

A new approach is developed for synthetic aperture radar (SAR) automatic target recognition based on convolutional neural network (CNN). In order to improve the low efficiency caused by fixed learning rate in CNN, the AdaDelta method is introduced to adjust the learning rate adaptively. The experimental results on Moving and Stationary Target Acquisition and Recognition (MSTAR) data sets show that convergence is significantly faster in proposed method than CNN with fixed learning rate.