mlclass-ex5

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.)

选择映射降低OFDM系统中PAPR的论文(Select map PAPR reduction in OFDM systems papers)

基于混合优化算法的车辆路径问题研究 matlab开发环境(matlab VPR Particle Swarm Optimization,PSO)

system identification (OPA)

里面有多个多普勒频移估计的高质量文章，不同的温江介绍不等的算法，有几个会有相似之处，在我看来这是非常好的多普勒频移估计的IEEE文章，希望对大家有用！(There are more than the estimated Doppler shift quality paper, different algorithms ranging Wenjiang introduction, there are several similarities, in my opinion this is a very good estimate of the Doppler shift of IEEE article, we hope to useful!)

一个基于dct变换的数字水印算法的源程序,可供进行数字水印学习和研究的学生及科研工作者学习参考(DCT-based digital watermarking algorithm transform the source code, available for study and research of digital watermarking students and researchers to study the reference)

this is matlab code for pprobality theory which is implemetatde in matab 7,6

隔振 减震 原理 描写了隔振方面的理论并且通过几个例子描述了简谐振动(The principle of isolation damping describe the isolation theory and describe a few examples of a simple harmonic motion)

模糊聚类和数据分析工具箱是一个集合的Matlab功能。它的提出​ ​ 是将一个给定的数据集为子集（称为集群），硬和模糊分区的意思是，这些之间的转换子集是脆的或渐进的。(The Fuzzy Clustering and Data Analysis Toolbox is a collection of Matlab functions. Its propose is to divide a given data set into subsets (called clusters), hard and fuzzy partitioning mean, that these transitions between the subsets are crisp or gradual.)

清华大学出版社出版MATLAB7.0教程 孙祥，徐流美，吴清主编(Tsinghua University Publishing House MATLAB7.0 tutorial Sun Xiang, Xu stream America, Wu Qing editor)