Projection

copulas参数估计方法的源代码。copulas为一种统计方法。(copulas parameter estimation method of the source code. copulas is a statistical method.)

剪切框架模型动力响应分析，即糖葫芦串形式的结构动力响应计算(dynamic response for shea frame model)

说明：  这是个关于滤波器实验，有学习滤波器的可以看看(This is about the filter, the experimental study filter can see)

Matlab的书籍的统计方法计算，这本书包含源代码(Matlab books, on the calculation of statistics, the book contains the source code)

i hav uploaed the signal creating code

the P300 (P3) wave is an event related potential (ERP) elicited in the process of decision making.

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.)

fast ICA的源文件 独立成分分析 MATLAB工具箱里也有 可以下载到工具箱 安装后就可以使用了(fast ICA Independent component analysis of the source file MATLAB toolbox is also available for download to install, ready to use the toolbox)

orical ppt学习，适合初学者，需要的可以下载哦(orical ppt)

basic fourier series gui for beginners