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matlab code for simulation SNR to verify capcity of channel

How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)

matlab初学教程，里边有对各个函数的介绍，并有实用介绍和说明。(matlab beginner tutorial, inside a description of each function, and a practical introduction and notes.)

基于形态学方法的图像分割文件，.m的源代码(Based on morphological image segmentation file,. M of the source code)

We present in this paper a new method for blind source separation which is adapted to the case where the sources have different morphologies. We show that the morphology diversity concept leads to a new and very efficient method, even in the p

part 4 schrodinger solve...

research papers for m tech

this is also another triangular membership function for fuzzy logic controlling

matlab一些常用的函数介绍,大家可以用一下(matlab function to introduce a number of commonly used)

说明：  这是冈萨雷斯数字图像处理MATLAB版本配套的源码，里版包含了书中所用到的所有作者编写的P文件，都可以直接应用，但不可以更改。(This is Gonzalez Digital Image Processing MATLAB version supporting source, where the book contains all the authors use to prepare the P document, can be applied directly, but not be changed.)