B(T-f)

P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波 P0309：运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理 P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理(P0301: digital image data display matrix and its Fourier transform P0302: Two-dimensional discrete cosine transform image compression P0303: gray-scale transformation of the methods used to enhance image contrast P0304: Histogram of homogenization P0305: simulated images by the Gaussian white noise and salt and pepper noise P0306: A two-dimensional median filter function medfilt2 by the salt and pepper noise to the image filtering P0307: the use of MATLAB function in the noise interference of filter2 images mean filter P0308: Wehner adaptive image filtering P0309: the use of five kinds of different gradient enhanced image sharpening method P0310: the image of the high-pass filter and mask to deal with P0311: the use of Butterworth (Butterworth) low pass filter on the subject of the image noise smoothing P0312: the use of Butterworth (Butterworth) high-pass filter for sharpening images)

fuzzy logic controller design

十分好的，数值优化工具箱，可以用来解决L1优化问题(numerical optimization toolbox)

该程序包包含了高光谱匹配中所用到的多种光谱匹配方法：光谱角度匹配，光谱相关匹配，相关角度匹配，梯度角度匹配，离散信息匹配，离散信息角度匹配等(The package includes several matching methods commonly used in high spectra remote Sensing。These are spectral angle matching(SAM）,spectral correlation matching(SCM),spectral correlation angle matching（SCA），SGA,SID,SID-SA and so on.)

for simulink park transform

读写segy格式和su格式的数据文件,对于从事地震数据处理的同行们很有用途哦(read and write file in segy or su format )

PSO优化控制算法在电厂控制（主汽温控制）中的应用(PSO optimization control algorithm for power plant control (main steam temperature control) in)

MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)

书籍《Understanding Molecular Simulation Algorithms to Application》的问题和例子，并附有代码(help learning ‘Understanding Molecular Simulation Algorithms to Applications’ case about molecular simulation, with results and codes)

this directory consist of simplify fuzzy artmap network m filse