针对目前隐身飞行器外形雷达散射截面(RCS)难以准确计算的问题，提出了一种基于目标外形几何特征和矩量法的飞行器r CS算法。
In order to solve the problem, a new algorithm for calculating RCS is presented based on the geometrical characteristic of target aircraft configurations and the method of moment (mom).
利用条件矩的性质特征刻画伽玛分布，负二项分布，广义混合指数分布，广义混合几何分布。
By using conditional moments, the author characterized the Gamma, Negative Binomial, Generalized Mixed Exponential and Geometric distributions respectively.
根据不同种类病虫骨架的几何矩特征，应用神经网络进行病虫识别。
According to the quadrature feature of different pests skeletons, a new method of insect pests recognition based on the combination of Mathematical Morphology and Neural Networks is proposed.
利用散射体的几何和物理特征，减少用矩量法求解散射场过程中所需要的存储量和计算时间，是当前具有理论和实际意义的重要课题。
It is of both theoretical and practical importance to reduce the storage and CPU time of moment methods by utilizing the geometrical and physical features of the scatterer.
分析了舰船目标的几何特征和不变特征，为满足实时性要求，使用一组统一的相对矩来计算特征量。
Geometry character and invariant character of ship target is analyzed and a united relative invariant moment is used to calculate the feature to meet real-time requirements.
优化特征选择，选定面积、周长、长轴、短轴、欧拉数、几何矩等共12个特征参数作为神经网络输入向量进行分类试验。
Optimization of feature selection, we select area, perimeter, long axis, short axis, Euler number, geometric moments, and a total of 12 feature parameters as input vector.
优化特征选择，选定面积、周长、长轴、短轴、欧拉数、几何矩等共12个特征参数作为神经网络输入向量进行分类试验。
Optimization of feature selection, we select area, perimeter, long axis, short axis, Euler number, geometric moments, and a total of 12 feature parameters as input vector.
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