randht

Tsai标定法的matlab实现 完成图像坐标到世界坐标的转换(Tsai calibration method to achieve the completion of the matlab image coordinate to world coordinate conversion)

各种分类器的工具包，包括贝叶斯分类器，k-means分类器等！(Various classifier toolkit, including the Bayesian classifier, k-means classifier, etc.!)

神经网络的使用方法，希望对大家有用，适合有基础的学生自己研究(Use of neural networks, we want to be useful for students who have their own research foundation)

说明：  matlab code for cognitive radio

说明：  改进型的人工势场matlab代码，有注释(Oussama Khatib Real Time obstacle Avoidance for Manipulators and Mobile Robots. Proc of The 1994 IEEE.)

用户提供样本数据后，对样本数据做c均值frm聚类分析。(c均值聚类)

说明：  灰色模型预测是在数据不呈现一定规律下可以采取的一种建模和预测方法，其预测数据与原始数据存在一定的规律相似性(Grey model prediction is a kind of modeling and prediction method that can be adopted when the data does not show certain rules. There is certain regularity similarity between the prediction data and the original data)

说明：  在matlab环境下生成一个正方形中心嵌套一个圆，并利用curvelet变换显示出其各个子层的系数图，良好的体现了curvelet变换的各向异性的性质。(In the matlab environment to generate a nested square center of a circle, and the use of curvelet transform shows that its coefficient of sublayer maps, a good reflection of the curvelet transform the nature of the anisotropy.)

DEMO MSER WITH DATA OF IDCAR 2015

该算法是以粒子群中粒子的收敛特性为基础,依据量子物理理论提出的,改变了传统粒子群算法的搜索策略,可使粒子在整个可行解空间中搜索寻求全局最优解。同时该算法的进化方程中不需要速度向量,而且进化方程的形式更简单,参数较少且容易控制。对两个算例进行仿真测试,证实该算法可有效解决经济负荷分配问题 性能对比显示,该算法求得的解优于已有的改进粒子群算法及其它优化算法所求得的解。(The algorithm is based on convergence particle swarm particle basis, according to the theory of quantum physics, particle swarm algorithm has changed the traditional search strategies, allow the particles throughout the feasible solution space search seek the global optimal solution. Meanwhile, the algorithm does not need velocity vector evolution equations, and evolution equations simpler and less parameters and easy to control. Two examples of simulation tests confirmed that the algorithm can effectively solve the economic load allocation performance comparison shows that the algorithm is superior to existing solutions obtained improved PSO algorithm and other optimization algorithms obtained solution.)