DIJKSTRA

维纳滤法实现语音去噪的两种算法 适合学习语音信号编码的(Wiener filtration voice denoising algorithm)

实现六自由度并联机器人的运动控制 simulink仿真(Implementation of 6 dof parallel robot movement control simulink simulation)

matlab傅里叶级数的代码，注意不是傅里叶变换(Fourier series code, note that not Fourier transform)

基于PCA算法的matlab源代码，适合初学者，可以快速学习PCA方法(Based on PCA algorithm matlab source code, suitable for beginners, you can quickly learn PCA methods)

说明：  eemd算法原程序及举例，用于信号分解，在emd基础上优化程序(EEMD algorithm original program and examples for signal decomposition, optimization program based on EMD)

说明：  Matlab编写BPSK信号通过AWGN信道的仿真过程(Matlab write BPSK AWGN channel signal through the simulation process)

matlAB中的simulink工具，具有可视化的特点，仿真易操作，简单可行(MATLAB大全- 宜配网的SIMULINK工具，具有可视化的特点，仿真易操作，简单可行)

说明：  本工具箱包含非线性方程组求解的程序代码，通过调用函数可求解相关方程的数值解，适合MATLAB初学者调试(This kit contains the nonlinear equations of the program code, by calling the function can be related equation for solving the numerical solution, suitable for beginners debug MATLAB)

make big-endian data files for grads

In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.