tuxiangchuli

统的联合概率数据关联算法(IPDA)是在密集杂波环境下的一种良好的多目标跟踪算法， 但它是针对单传感嚣对多目标跟踪的情况下使用，不能直接用于多传感器对多目标的跟踪。针对这 一问题，文中提出了一种适用于多传感器多目标跟踪的JPDA算法，它以极大似然估计完成对来自 多传感器的测量集合进行同源最优分划，然后采用JPDA方法对多目标进行跟踪。经过理论分析和 仿真试验，证明了该方法能有效地进行多传感器多目标的跟踪，且具有算法简单、跟踪精度高、附 加的计算量小等优点。(Abstract)m JointProbabilisticDataAssociation(JPDA)solves single sensormultitatgcttrackingin ClUtter,butitc锄not bc used directly in mnitisensor multitarget tracking．喇8 paper presents a method to implement multi—sensor multi—target tracking by combining maximum likelihood estimation wim JPDA The maximum Iikelihood estimation is used to classify the same source observations at one time into the same set,and血en JPDA implements multi—target uacking after the position fitsed．The theory analysis and computer simulation show that this algorithm may achieve multi—sensor multi—target tracking perfectly with low calculation load added and higher precision 。)

齿轮箱故障诊断BP模型的Matlab程序(Gearbox fault diagnosis of BP model Matlab program)

基于MATLAB的谐波电流检测方法的建模与仿真(MATLAB-based harmonic current detection method of modeling and simulation)

MATLAB 学习资料,关于GUI界面编程好书(MATLAB learning materials, a good book on the GUI interface programming)

利用LMS算法来进行盲信号分离处理的程序(Using the LMS algorithm for blind signal separation processing procedures)

photoshop,基于matlab的GUI界面，实现对图像的处理。包含背景处理，化直方图，fft，加噪声等等。(matlab-based GUI interface, photoshop, image processing. Contains background processing, histogram, FFT, plus noise.)

matlab例程，根轨迹，微分方程等 (Matlab routines, root-locus, differential equations, etc.)

matlab环境下建立威胁模型，规划路径，回避威胁(path plan)

模型辨识 模糊神经网络 T-S模型 输入输出 前提参数 结论参数(Model Identification of TS Fuzzy Neural Network model input and output parameters of the premise parameters Conclusion)

Matlab source codes for the regularized linear discriminant analysis (R-LDA)，Author: Lu Juwei，Bell Canada Multimedia Lab, Dept. of ECE, U. of Toronto，Released in 01 November 2004 (Matlab source codes for the regularized linear discriminant analysis (R-LDA), Author: Lu Juwei, Bell Canada Multimedia Lab, Dept. Of ECE, U. of Toronto, Released in 01 November 2004)