The dissertation is the study of the target recognition and orientation which has change of Angle, translation and scale under the simple background, based on the neural networks.
本文研究了简单背景下，发生尺度、角度、位置变化的目标的神经网络识别、定位方法。
In fuzzy control, according to the actually obstacle position and the Angle between the target orientation and the robot's direction of movement, we give the reaction rules of the robot.
本文采用模糊控制的方法控制移动机器人的前进方向，在模糊控制中根据障碍物的实际位置及机器人运动方向与目标点夹角的不同情况，给出了机器人的反应规则。
A novel scheme of target enhancement in high-resolution polarimetric SAR imagery is proposed in this paper, which is based on the targets polarization orientation Angle feature.
针对高分辨极化SAR目标增强问题，提出一种利用极化方位角特征的增强方法。
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