MATLAB_program_syntax_programming_classic_design

这是一个关于matlab程序的实例，里面详细介绍了一些函数的使用 (This is a procedure on the matlab example, which detailed the use of some function)

Plots the AVaR versus different confidence levels given a Profit-Loss vector. It calculates AVaR assuming a Gaussian distribution for the P/L vector.

watermarking using lsb replacement

I THINK THAT ALL WHAT I WANT IS THIS

最优剪枝极限学习机的matlab工具箱，内有源码课直接拿来修改使用(Extreme Learning Machine optimal pruning matlab toolbox, there are lessons directly used to modify the source code)

infinite HMM Refer to Beal s Paper Applying Gibbs Sampling in inference the number of states of HMM is changeable in this algorithm, based on Dirichlet Proce(infinite HMMRefer to Beal s PaperApplying Gibbs Sampling in inferencethe number of states of HMM is changeable in this algorithm, based on Dirichlet Proce)

巴特沃斯滤波器MATLAB仿真程序，分析，绘图，手动设置参数(MATLAB simulation program Butterworth filter, analysis, mapping, set the parameters manually)

ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。 基本思想： 在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。 (Description This is an example of the basic Active Shape Model (ASM) as introduced by Cootes and Taylor, with multi-resolution approach. Basic idea: The ASM model is trained from manually drawn contours in training images. The ASM model finds the main variations in the training data using Principal Component Analysis (PCA), which enables the model to automatically recognize if a contour is a possible/good object contour. Also the ASM models contains covariance matrices describing the texture of the lines perpendicular to the control points when in the correct positions. After creating the ASM model, an initial contour is deformed by finding the best texture match for the control points. This is an iterative process, in which the movement of the control points is limited by what the ASM model recognizes from the training data as a "normal" object contour. Literature: - Ginneken B. et al. "Active Shape Model Segmentation with Optimal Features", IEEE Transactions on Medical I)

神经网络去噪 matlab程序 神经网络去除随机脉冲干扰(neural network denoising Matlab neural network removal procedures random pulse interference)

Am Modulation M-File Code