leastsq

说明：  求解多目标车辆路径问题的遗传算法的小文章(based on GA solve the mutil-objects problem with the help of time window)

自己编写的利用霍夫变换检测满足一定条件直线的matlab程序，对各个参数进行了详细说明(I have written using Hough transform to detect straight line to meet certain conditions, matlab program for a detailed explanation of each parameter)

FBMC滤波器组多载波系统的方针程序，采用OQAM调制。可以和OFDM系统做个对比(FBMC （filter bank multi-carrier) OQAM)

非常不错的小波程序(very good wavelet procedures!)

windmill turbine models

蒸气幻想简单挂机脚本.jar供研究Script的玩家学习(steam fantasy simple hook script. Script jar for research study of the player. .)

lingjian.m-----蒙特卡罗方法 lingjian.m使用零件初始值，用蒙特卡罗方法算出总费用。其中使用了自己编制的正态分布随机数发生器产生正态分布随机数。lingjian.m是对蒙特卡罗方法的一次练习。 accyouhua为标定值的函数，而lingjian不是一个函数，在其中已给出了一组标定值的值。 退火确定标定值/unitanneal()----模拟退火 连续型多个变量组合优化问题 这是对模拟退火方法的一次练习，结果证明模拟退火确实是一个行之有效的方法。 当参数选择较好时（一般也伴随着运行时间的加长），模拟退火的结果较好，然而用MATLAB的FMIMCON()一般可达到更高的精度。(lingjian.m---- Monte Carlo method. 氀椀渀最樀椀愀渀.m Part initial value, using the Monte Carlo method to calculate the total cost. The preparation of their own normal distribution random number generator to generate normally distributed random numbers. lingjian.m is the first practice of the Monte Carlo method. accyouhua calibration value the function lingjian not a function, which gives the value of a set of calibration values. Annealing to determine the calibrated value/unitanneal ()---- Simulated Annealing 吀栀攀 continuous multiple variables combinatorial optimization problems 吀栀椀猀 is an exercise of the simulated annealing method, the results show that the simulated annealing is an effective method. 圀栀攀渀 the parameter selection is better (generally accompanied by a longer running time), simulated annealing results, however using MATLAB FMIMCON () generally achieve higher accuracy.)

讲述了现在机械故障诊断中用到的常用时频分析方法，如短时fft 魏格纳维尔分布 小波变换 HHT等，里面含有例子和详细说明，对初学者帮助很大。(Tells the now commonly used in mechanical fault diagnosis frequency analysis methods, such as short-time wavelet transform fft Wigner distribution HHT Louisville, etc., which contains examples and detailed instructions, very helpful for beginners.)

Finding the Nearest Orthonormal Matrix In some appoaches to photogrammetric problems (perhaps inspired by projective geometry), an estimate M of an orthonormal matrix R representing rotation is recovered. It is then desired to find the “nearest’’ orthonormal matrix. While this two step approach — first finding a “best fit’’ matrix without enforcing orthonormality,and then finding the nearest orthonormal matrix — is not to be recommended, it may be of interest to find a solution to this problem nevertheless.

matlab实现彩色图像的余弦压缩变换，分阈值不同显示(matlab color image compression cosine transform, threshold different display)