MATLABstudy

backpropagation algortihm for fisher data

简化的JPDA算法，提高效率，速度提高不少(Simplified JPDA algorithm, improve efficiency)

物理光学法计算RCS，Radar And Laser Cross Section Engineering(Radar And Laser Cross Section Engineering)

OFDM系统仿真，所用的源代码 ，用matlab软件进行仿真(OFDM system simulation, using the source code with matlab software simulation)

视频 跟踪 修改的程序 关于视频的目标跟踪(Video tracking procedures for amendment of the video target tracking)

自己搭的一个pmsg模型，能实现最大功率点跟踪(D-PMSG MODEL is built by myself，it can achieve mppt )

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.)

Smart Antennas for Wireless Communications（中文版程序）(Smart Antennas for Wireless Communications)

说明：  这是为想学习Matlab的学习者准备的足够练习题，实例子，有了它们，你可以很好的去练习而不是纸上谈兵。(This is to prepare learners want to learn enough Matlab exercises, case children, with them, you' re good to practice rather than on paper.)

Sinusoidal and Space Vector Pulse Width Modulation for Inverter