BP

说明：  用Matlab实现蒙特卡罗模拟的源程序,非常的好用(Monte Carlo simulation using Matlab realization of the source program, very easy to use)

光伏发电功率主要受太阳辐照度影响，所以准确预测太阳辐照度对光伏功率预测十分重要。程序采用小波分解先对辐照度数据进行分解，然后再用bp神经网络对分解的辐照度数据分别预测，再组合作为最后的预测结果。(Photovoltaic power generation is mainly affected by solar irradiance, so accurate prediction of solar irradiance is very important for photovoltaic power prediction. The program uses wavelet decomposition to decompose the irradiance data, then uses BP neural network to predict the decomposed irradiance data separately, and then combines them as the final prediction result.)

湍流统计特性检验，用于通量数据质量描述 湍流统计特性检验，用于通量数据质量描述(Examine the statistical properties of turbulence for the turbulent fluxes describe the statistical properties of the data quality tests for data quality description flux)

生成Intel Hex file的MATLAB源程序(MATLAB source generates Intel Hex file)

说明：  particle swam optimazation technique

视频图像的滤波，算法比较简单，可以有效的滤除掉图像的高斯噪声、椒盐噪声(Video image filtering algorithm is relatively simple, and can be eliminated effectively image Gaussian noise, salt and pepper noise)

通过AR模型模拟得到风荷载，其模拟是有davenport风速谱得到的(By AR model simulation of wind loads, and its analog davenport wind speed spectrum)

coding for generating a mel filter bank for a given frequency vector

说明：  利用那个matlab进行图像处理的几个常用的.m文件，需要自己考进自己的处理目录就可以正常使用了。(Using the matlab image processing of several commonly used. M files, you need to test their processing into its own directory to be normal use.)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)