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正交频分复用（OFDM）的完整系统仿真程序，值得学习参考(Orthogonal Frequency Division Multiplexing (OFDM) is a complete system simulation program, it is worth learning reference)

灰度 GM（1.1）模型：灰色系统其内部一部分信息已知，另一部分信息未知或不确定。对既含有已知信息又含有不确定信息的系统进行的预测，也就是对在一定范围内变化的、与时间序列有关的灰过程进行 预测。(Gray GM (1.1) model of grey system: the internal part of the information known, the other part of the information is unknown or uncertain. In which there are both known information and uncertain for the prediction information system, is also the process of gray change in a certain range, with the time series related to Prediction.)

谱估计的典型算法周期图法的程序,给出了具体的程序代码(periodogram method)

standard code for PSO

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.)

三电平逆变器仿真，不可多得的资料，欢迎大家下载(three-level inverter simulation, a rare, welcome you download)

说明：  模糊C均值聚类的MATLAB程序，有详细中文注释，对初学者很有帮助。(Fuzzy C-means clustering of the MATLAB program, a detailed English notes, very helpful for beginners.)

K Means Cluster Matlab Source Code

小数分频PLL的matlab源代码，包含二阶sigma-delta调制器的源码。(Fractional PLL the matlab source code)

去伪PID控制算法，一重新型的PID控制算法(It is a new pid control method)