matlab03_Fig

模式识别中用matlab实现c均值的计算，分类实现的算法。(matlab，c-means fuction)

DTFT的实现 适用于初学者的适用于初学者的适用于初学者的(Implementation of DTFT)

matlab有限元编程75个案例，梁、板等结构，三角形，四边形等单元(matlab finite element program 75 cases, all very powerful, just always just a single)

pca的matlab程序及其资料，很详细的叙述了算法(pca matlab program and its data, it is a detailed description of the algorithm)

三电平SVPWM的simulink仿真，可以用于各个闭环(Three-level SVPWM simulink simulation can be used for each closed loop)

说明：  设基带码元传输间隔为0.1秒，FSK调制参数分别设置频率间隔为5Hz和20Hz，相位分别设置为不连续的和连续的两种。试对比观察4元FSK调制输出等效低通信号的功率频谱。(Let the baseband symbol transmission interval is 0.1 seconds, FSK modulation parameters are set the frequency interval of 5Hz and 20Hz, respectively, set to the discontinuous phase and continuous two. Observation of test 4 yuan FSK modulation output equivalent low pass signal of the power spectrum.)

利用labview与matlab结合实现人脸定位算法 置入mathscript(Labview matlab combined with the use of a face localization algorithm implementation into mathscript)

Matlab functions implementing non-parametric local linear smoothing (LLS) for one-dimensional curve fitting: yi = f(xi) + ei for i = 1, 2, ..., n. The toolbox contains: (i) the usual LLS estimator, see e.g. [1] (ii) a jump-preserving (two-sided) LLS estimator proposed in [2] (iii) a modified version of the two-sided LLS proposed in [3].(Matlab functions implementing non-parametric local linear smoothing (LLS) for one-dimensional curve fitting: yi = f(xi)+ ei for i = 1, 2, ..., n. The toolbox contains: (i) the usual LLS estimator, see e.g. [1] (ii) a jump-preserving (two-sided) LLS estimator proposed in [2] (iii) a modified version of the two-sided LLS proposed in [3].)

matlab中极坐标函数的改进，坐标轴刻度可以为负数，输入参数见注释，有问题email联系，可在matlab命令行中直接运行，如： my_polar2([0,20,30]*pi/180,[-10,0,10], -r ,-20,30)(Matlab polar coordinates function improved, axes calibration can be negative, the input parameters, see Notes email problems can be contacted in Matlab command line direct operations, such as : my_polar2 ([0,20,30]* pi/180 [-10,0,10],- r,-20,30))

matlab code for image segmentation