FIG002

自己收集的粒子滤波程序，包括基本的程序，卡尔曼滤波以及改进的算法。(Their own procedures for the collection of the particle filter.)

本文件中包含的代码是使用Bayesian compressive sensing 理论对图像降噪，修复的程序(his package includes 4 folders. Folder toydata contains core code and demo of the original BRPCA Model Folder MarkovDependency contains core code and demos of the modified BRPCA Model with Markov dependency employed Folder NonstationaryNoise contains core code and demos of the modified BRPCA Model with Markov dependency employed and the noise variances are different from contuguous frames. Folder Videodata contains the video data used by the experiment.)

Trajectory optimization

this file is yee method to simulation of plane wave propagation

针对常规测速方法，M法与T法的研究与探讨，分析了两种方法的误差来源，指出了问题本质，并提供了仿真图例。(For the conventional measurement methods, M Law and T The Study and discussion of the two methods of error sources, pointed out the nature of the problem and provide a simulation of legend.)

this is the mat program for library

soccer robot simulation based matlab

4阶经典Runge-Kutta格式解常微分方程,Romberg(龙贝格）法求函数的积分,三阶样条插值（一阶导数边界条件）,定步长梯形法求函数的积分,矩阵A的伴随矩阵, Lagrange插值法数值求解,Newton迭代法解非线性方程f(x)=0(Fourth-order Runge-Kutta classic format solution of ordinary differential equations, Romberg (Romberg) method for function points, third-order spline interpolation (first derivative boundary conditions), fixed-step trapezoidal method for integrating functions, matrix A adjoint matrix, Lagrange interpolation method for numerical solution, Newton iterative method for solving nonlinear equations f (x) = 0)

针对mean shift 跟踪方法中存在的光照变化不稳定问题， 提出了基于梯度特征与彩色 特征相融合的mean shift 跟踪方法。首先分别提取目标的梯度特征和彩色特征，利用多尺度的相似度 计算方法进行特征的匹配，然后通过最大化相似度对目标进行跟踪。通过物体和人体等运动目标的跟 踪，验证了改进的跟踪算法在光照变化情况下的鲁棒性优于原有的算法，显著降低了跟踪位置误差。(The instability of the light changes in the mean shift tracking method, the mean shift tracking method based on gradient features and color characteristics of fusion. First extract gradient features and color features of the target, the similarity calculation method using multi-scale feature matching, and then maximize the similarity of the target track. Through the tracking of objects and people moving target, verify the robustness of the improved tracking algorithm in the case of illumination changes is better than the original algorithm significantly reduces the tracking position error.)

基于四边单元速度传热问题程序,入门程序，简单易懂，适合初学者对该方法编程的一个初步认识(Based on four sides of the unit rate of heat transfer procedures, entry procedures, easy to understand for beginners to the method of programming a preliminary understanding)