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reglement_concours_Tss2015 -

多用户检测的MATLAB实现 希望对大家学习有帮助(duoyonghujiance)

说明：  下面的程序是求多项式y=x^6-10x^5-26x^4+344x^3+193x^2-1846x-1680在区间[-8,8]的最小值，误差不超过0.001。对于这个复杂的多项式，可先用matlab绘制函数的大概曲线，确认函数的最小值大概处于[-8,8]之间，再用本程序求出精确解。 (The following procedure is a polynomial y = x ^ 6-10x ^ 5-26x ^ 4+344 x ^ 3+193 x ^ 2-1846x-1680 in the interval [-8,8] of the minimum error is not more than 0.001. This is a complex polynomial, can first draw function with matlab about curves, to confirm the function of the minimum are probably in [-8,8] range, and then find the exact solution of this program.)

精通MATLAB数字图像处理与识别第二章练习代码(Proficient in MATLAB digital image processing and recognition chapter exercises code)

这是一本书的一个章节的源代码关于图像优化的我觉得真的挺好的(This is a chapter of a book about image optimization of the source code, I think it is quite good)

its about svpwm dtc of an induction motor drive

MATLAB程序源码，用于读取地震波数据segy格式的文件(read seis-segy file)

完成了对OFDM（正交频分复用）通信系统从信号输入，编码，发射，解码，求误码率的全过程，压缩包中word文件为系统仿真报告，其他为matlab代码。(Completes the OFDM (Orthogonal Frequency Division Multiplexing) communication system the signal input, encoding, transmitting, decoding, bit error rate of the entire process required)

Function to implement Linear Discriminant Analysis Usage:- [Xnew,V,mX,D] = lda(X,index,mX) [V,D] = lda(X,index) where:- X = concatenated grand profile vectors (GPV) i = class index of each vector Xnew = new feature vectors P = eigen vectors mX = mean of GPV (optional in input) D = eigen values

粗糙惩罚算法，此算法能够分辨光谱数据中的坏点，并对坏点加以惩罚，即减小该点的权重值，从而使得数据更加真实平滑。(Roughness Penalty Smoothing)