phd

This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. (This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. )

各种观测矩阵，高斯，伯努利，部分哈德玛，随机，托普利兹，循环，部分傅里叶矩阵(Various observation matrices)

matlab实现PCA进行的人脸识别源程序，基本的功能实现，做为基础(matlab realize PCA for face recognition source code, the basic function of the realization, as a basis for)

matlab source code for implementing watermarking techniques.

说明：  扩展卡尔曼滤波与粒子滤波滤波性能比较的源程序(Extended Kalman filter and particle filter source)

GaussSeidel search algorithm matlab

独立分量分析，利用此程序可以提取独立分量(independent component analysis, the use of this procedure can be extracted ICA)

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 matrix display and Fourier Transform P0302 : Two-dimensional discrete cosine transform image compression P0303 : Gray used a new method to enhance the contrast of the image P0304 : histogram equalization P0305 : Simulation images by white Gaussian noise and Impulse noise impact P0306 : 2D median filtering function medfilt2 right by the Salt and Pepper image noise filtering P0307 : MATLAB filter2 the function of noise interference by the image filtering P0308 : Image Adaptive Filter Weiner P0309 : use five different gradient Enhancement Act for image sharpening P0310 : Images of the high-pass filtering and mask handling P0311 : use Butterworth (Butterworth) low-pass filter to noise interference by the image smoothing P 0312 : Butterworth (Butterworth) high-pass fi)

小波分析理论与matlab7实现的例程,第10章一维小波变换的MATLAB实现(Wavelet analysis theory and realize matlab7 the routines, Chapter 10, one-dimensional wavelet transform MATLAB realize)

实现数字信号处理中的常用功能 matlab平台(implementation of widely used functions in the field of Digital Signal Processing. Platform: Matlab 2007b)