首页> 外文期刊>Lobachevskii journal of mathematics >Robustness of the Algorithm of Identification of the Type of Dynamic Object Found at the Finite Sequence of 2D Background Frames of the Optoelectron Device
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Robustness of the Algorithm of Identification of the Type of Dynamic Object Found at the Finite Sequence of 2D Background Frames of the Optoelectron Device

机译:光电子装置的2D背景帧有限序列发现的动态对象识别算法的鲁棒性

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摘要

Here are proposed robustness characteristics of the algorithm of identification of the type of the dynamic object (DO) and the law of probability distribution of identification sufficient statistics, formed by the algorithm under prior uncertainty. The law is applied for verification and validation of the algorithm. Wavelet fractal correlation algorithm (WFCA) implements vectorial criterion of ratio of likelihood functions of simple alternative hypotheses—types of DOs, this criterion being invariant to specific features of DO motion trajectories. The likelihood functions are reconstructed by simulation according to sufficiently representative complexes of implementations of fractal dimensions, energies, wavelet spectra and maximum eigenvalues of biased correlation matrices as functional of the measured coordinates of spatial attitude of various types of real DOs located by the optoelectron device (OED). The simulation proved robustness and high efficiency of the algorithm of identification of the type of DOs.
机译:这里是由在现有不确定性下算法形成的动态对象(DO)类型的识别算法的识别算法的稳定性特征,并由识别足够统计的概率分布。法律适用于算法的验证和验证。小波分形相关算法(WFCA)实现了简单替代假设类型的似然函数的似然函数比率的矢量标准,该标准对DO运动轨迹的特定特征不变。根据偏置相关矩阵的分形尺寸,能量,小波频谱和最大特征值的实现的足够代表性复合物,通过偏置相关矩阵的最大特征值作为所测量的各种类型的实际DOS的空间姿态的测量坐标的功能( OED)。仿真被证明了识别识别算法的鲁棒性和高效率。

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