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A Stochastic Graph Evolution Framework for
Robust Multi-Target Tracking
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ML法能够很好的估计信号的信噪比,滤波求和方式实现宽带波束形成，多目标跟踪的粒子滤波器。- ML estimation method can be a good signal to noise ratio, Filtering summation way broadband beamforming, Multi-target tracking particle filter.
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采用波束成形技术的BER计算，调试通过可以使用，多目标跟踪的粒子滤波器。- By applying the beam forming technology of BER Debugging can be used, Multi-target tracking particle filter.
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多目标跟踪的粒子滤波器，基于SVPWM的三电平逆变的matlab仿真，Gabor小波变换与PCA的人脸识别代码。- Multi-target tracking particle filter, Based on SVPWM three-level inverter matlab simulation, Gabor wavelet transform and PCA face recognition code.
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