2.5 (2)

matlab编写的频域分解法程序，可以在此基础上进行改进.(matlab prepared frequency domain decomposition procedures can be improved on this basis.)

一个快速k均值彩色图像的分割算法，运行环境是matlab！(A fast k-means algorithm for color image segmentation, the operating environment is matlab!)

在数值分析中，比较CG和Lanczos的计算结果.并比较了不同特征值情况下的计算结果。(in numerical value analyse, Compare the CG and Lanczos, futher more, we compare the CG and Lanczos in the different eigenvalue.)

判断一个数是否为素数。可以作为分析研究素数编程的人参考。(To determine whether a number is prime. Analysis of prime numbers can be used as programming easy reference)

说明：  a file to genreate 16psk signal

数值积分中matlab的实现，其中包括拉格朗日插值、辛普森插值等基本算法。(Numerical integration in matlab realization, including Lagrange interpolation, Simpson and other basic interpolation algorithm.)

matlab的数理统计工具箱，有很强的实用价值，适合当做应用学习库来进行保留(Matlab statistics toolbox, has a strong practical value, suitable for application to retain as learning library)

坐标变换，实现3/2和2/2变换。异步电动机矢量控制中使用的(Coordinate transformation, to achieve 3/2 and 2/2 transformation. Vector control induction motor used)

这是一个支持向量机的matlab源代码，可以进行对数据的预测。(This is a support vector machine matlab source code, you can forecast data.)

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 lingjian.m part the initial value, using the Monte Carlo method to calculate the total cost. The use of the preparation of their own normal distribution random number generator to produce a normal distribution of random numbers. lingjian.m yes to the first practice of the Monte Carlo method. accyouhua calibration function, and lingjian is not a function, which has given the value of a set of calibration values​ ​ . Annealing to determine the calibration value/unitanneal ()---- Simulated Annealing Combinatorial optimization problem of continuous multiple variables This is a practice of simulated annealing method, the results show that simulated annealing is an effective method. Parameter selection is better (usually accompanied by longer running time) the results of simulated annealing, however the MATLAB FMIMCON () generally achieve higher accuracy. )