matlab50

controling stepmotors using matlab

IEEE57节点电力系统标准参数和潮流数据(IEEE57 node power system standard parameters and trend data)

Matlab 计算有限元的一些程序，期望对大家有些帮助！！！！(Matlab finite element calculation of some of the procedures, expectations of you some help! ! ! !)

A Gabor-filtering method for describing textural features is proposed, which applies the physical properties of a probability wave to probability transformation, and computes textural features 2) An adaptive strategy for feature and filter selection, and feature weighting, is proposed, which utilizes a user’s relevance feedback to reduce the redundancy in the representation and incorporate the user’s information needs in image retri 3) Integrating both schemes (the Gabor-filtering method and the adaptive strategy) for content-based mammogram retri is suggested

chaos map : Logistic map

基于高斯线性的概率密度函数滤波估计，以此为蓝本有很多改进或类似的算法，比如CDKF-PHD等(Based on Gaussian probability density function of the linear filter estimation, there are a lot of improvements as a blueprint or similar algorithms, such CDKF-PHD, etc.)

MATLAB进行模糊统计，得到模糊分布(隶属函数)近似解析表达式(MATLAB fuzzy statistics, get fuzzy distribution (membership function) approximate analytical expressions)

说明：  光流法实现无人驾驶前方目标识别与目标追踪，用MATLAB编写(Optical flow method for target tracking)

实现两个稀疏矩阵相乘(效率高于早期的Matlab自带的程序)，Matlab编程 (SSMULT is a simple stand-alone MATLAB mexFunction that computes C=A*B where both A and B are sparse. It is typically faster and always uses less memory than C=A*B in MATLAB 7.4 (or earlier). Works on MATLAB 6.1 to the current version. Untested on earlier versions of MATLAB. It is a built-in function in MATLAB 7.6 and later for C=A*B when both A and B are sparse. )

Traveling Salesman Problem (TSP) has been an interesting problem for a long time in classical optimization techniques which are based on linear and nonlinear programming. TSP can be described as follows: Given a number of cities to visit and their distances from all other cities know, an optimal travel route has to be found so that each city is visited one and only once with the least possible distance traveled. This is a simple problem with handful of cities but becomes complicated as the number increases.