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Tracking of visual phenomena is hard. Very, very hard. And frustrating. You should try not to get discouraged by poor tracking results, but rather concentrate on the specific reasons why your tracker may not be performing well. Is the bad performance predictable from the theoretical properties of the tracker? If so, that s a valuable observation that will serve you well in the future

升压型boost电路simulink仿真分析源程序，220输入，400V直流输出(Boost boost circuit simulation simulink source, enter 220, 400V DC output)

说明：  用matlab实现基于LBG算法的向量量化编码(Matlab by LBG algorithm based on vector quantization coding)

本算法描述了cdma反向信道的功率控制问题，包括基站以及移动台的功率控制以及相关的文章(description of the algorithm cdma reverse channel power control, , including base stations and mobile stations of the power control and the relevant article)

article about a dvr system

关于自振动仿真的源代码，可以看看，第一传求关注，支持。(Source Courseware)

说明：  基于matlab的振动数据处理教程及源代码(Matlab based vibration data processing tutorial and source code)

这是matlab灰度差程序，其中包含阈值的获得和镜头突变的检测，适合初学者(This is a gray-scale difference matlab program, which includes access to the threshold of detection of mutations and lens, suitable for beginners)

it is fcm kidney segmentation

ofdm的基本原理 及MATLAB仿真(ofdm simulation of the basic principles and MATLAB)