chaotic lyapunov

This is a MATLAB Simulation for obtaining conduction and switching losses in Three-Phase OHSW(optimized harmonic stepped wafeform) cascaded 9-level inverter.The simulation has been done in several SUBSYSTEMS.The first one produces switching functions based on OHSW.The second one is the 9-level inverter model.the third and fourth obtain load and switching devices currents respectively.The fifth and sixth obtain switching and conduction losses.

函数名称：matlab求积分函数。函数功能：该函数需要输入自变量，函数，积分下限，积分上限。非常方便。(Function name: matlab for integral function function: this function need to enter the independent variable, function, integral floor, integral upper limit is very convenient. )

基于稀疏表示的正交最小二乘法，使用的语言是matlab，应用比较广阔，设计信号处理中的信号回归，图像处理的压缩等。(Sparse representation based on orthogonal least squares method, the language used is matlab, relatively broad application, design signal processing signal return, image processing, compression and so on.)

Haskell code defining syntax und semantics of the "while language" with welltyped predicates. Inspired by "Semantics With Applications" (Nielson).

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.)

thyristor firing in matlab

matlab video motion detection and tracking

小波滤波，可用于心电信号、脉搏波信号的滤波(Wavelet filtering, can be used for ECG, pulse wave signal filtering)

fisher线性分类代码。老师要我们自己做的，还不错哦(fisher linear classification code. Teacher wants us to make their own, and have a good oh)

关于捷联惯性导航传递对准的仿真程序，期待学术交流~谢谢分享~(Simulation program on Transfer Alignment of Strapdown Inertial Navigation and look forward to the academic exchange ~ Thank you for sharing ~)