chengxuheshuzu[1]

MATLAB2维小波变换经典程序，用DWT实现二维小波变换(MATLAB2-dimensional wavelet transform classical procedures, with the realization of two-dimensional wavelet transform DWT)

一个关于BPSK误码率仿真的程序，其中包括信号产生，加入高斯白噪声，和误码率计算！(One on BPSK BER simulation procedures, including the signal generated by adding Gaussian white noise, and bit error rate!)

Simple Matlab Script file(m file) for a unit PV cell.

针对SVM法线特征筛选算法仅考虑法线对特征筛选的贡献,而忽略了特征分布对特征筛选的贡献的不足,在对SVM法线算法进行分析的基础上,基于特征在正、负例中出现概率的不同提出了加权SVM法线算法,该算法考虑到了法线和特征的分布.通过试验可以看出,在使用较小的特征空间时,与SVM法线算法和信息增益算法相比,加权SVM法线算法具有更好的特征筛选性能.(Normal feature selection for SVM algorithm only considered normal for the contribution of feature selection, to the neglect of the characteristics of the distribution of feature selection have contributed to the lack of normal SVM algorithm based on the analysis, based on the characteristics of the positive and negative cases emergence of a different probability-weighted normal SVM algorithm, which takes into account the distribution and characteristics of normal. through the test can be seen in the use of smaller feature space, the normal and the SVM algorithm and information gain algorithm, normal weighted SVM algorithm has better performance of feature selection.)

本科毕业论文，基于非高斯性最大化的盲信号分离方法，适合本科生做毕业设计。(Undergraduate thesis, based on maximization of non-Gaussian signal separation method, suitable for undergraduate students to do graduate design.)

这个不用多说，现在非常流行的一种迭代压缩感知重建算法。(Needless to say this, now very popular an iterative reconstruction algorithm for compressed sensing.)

matlab 快速傅里叶变换，需要知道一组离散的数据。(this mtalab code can be used for fft)

压缩感知源代码，观测矩阵采用哈达吗变换。很好的入门代码(Compressed sensing the source code, you transform observation matrix using Hada. Good entry code)

riccati传递矩阵法算例，计算大转子的临界转速，固有频率(riccati example transfer matrix method to calculate the critical speed the greater trochanter, natural frequency)

matlab绘图。详细综合matlab的绘图方法，包括二维，三维绘图。以及相映的图象编辑功能。能从多角度对图象进行处理！(Matlab graphics. Detailed and comprehensive Matlab graphics, including 2D and 3D graphics. , And form a contrast image editing features. From the perspectives of image processing!)