solar_module

详细对比了几种小波去噪阈值的选取方法，对实际应用有一定的指导作用(Detailed comparison of several wavelet de-noising threshold selection method, the practical application of the guiding role of certain)

Its a new optimization algorithm particle swarm optimization with dynamic function analysis.

说明：  相关向量机（Relevance Vector Machine，简称RVM）是Micnacl E.Tipping于2000年提出的一种与SVM（Support Vector Machine）类似的稀疏概率模型，是一种新的监督学习方法。 它的训练是在贝叶斯框架下进行的，在先验参数的结构下基于主动相关决策理论（automatic relevance determination，简称ARD）来移除不相关的点，从而获得稀疏化的模型。在样本数据的迭代学习过程中，大部分参数的后验分布趋于零，与预测值无关，那些非零参数对应的点被称作相关向量（Relevance Vectors），体现了数据中最核心的特征。同支持向量机相比，相关向量机最大的优点就是极大地减少了核函数的计算量，并且也克服了所选核函数必须满足Mercer条件的缺点。(Relevance Vector Machine (RVM) is a sparse probability model similar to SVM (Support Vector Machine) proposed by Micnacl E. Tipping in 2000. It is a new supervised learning method. Its training is carried out under the Bayesian framework. Under the structure of prior parameters, it is based on Automatic Relevance Determination (ARD) to remove the irrelevant points, so as to obtain the sparse model. In the iterative learning process of sample data, the posterior distribution of most parameters tends to zero, which is independent of the predicted value. The points corresponding to non-zero parameters are called Relevance Vectors, which represent the most core features of the data. Compared with support vector machine, the biggest advantage of correlation vector machine is that it greatly reduces the computation amount of kernel function, and also overcomes the shortcoming that the selected kernel function must meet Mercer's condition.)

颜色空间的转换应用matlab编写的程序 很好用的程序(color space change use matlab wirite it is a good program)

cmac与pid并行控制在matlab中的编程(the cmac pid parallel control programming in matlab)

matlab编程实现线性预测编码（LPC)(Matlab programming linear predictive coding (LPC))

自己毕设做的基于三角载波的有源电力滤波器（APF）仿真，可供（apf和pwm整流器设计参考使用）(Do your own complete set of triangular carrier-based Active Power Filter (APF) emulation available (apf and pwm rectifier design reference))

说明：  混沌计算程序源文件——包括计算Lyapunov指数的5种方法：C-C算法,最小数据量算法，G-P算法，关联维数法，互信息量法。(the original programs to calculate chaos in order to count the Lyapunov index out. Including 5 such methods: c-c method, minimum data method, G-P, mutual information method and correlation dimentional method.)

是粗糙集中很不错的代码。。。。这里面还含有粗糙集的论文 愿意与大家共享(Rough set is very good code. . . . There also contains a rough set of papers are willing to share with you)

TolPac=1 输入数据块数 PacketLen=10 每块的符号数目 M=64 调制指数 SNR=20 NFFT=256 Length of IFFTCpLength=16 Length of Prefix NSubc=64 Number of subcarriers freoff=0.5 归一化频偏2.25,phaseoff=0.1 (TolPac = 1 input data blocks the the PACKETLEN 10 of the span per block, the number of symbols M = 64 modulation index SNR = 20 NFFT = 256 the length of IFFTCpLength = 16 Length of Prefix NSubc = 64 Number of subcarriers freoff = 0.5 the normalization frequency offset 2.25 phaseoff = 0.1 )