LMI-MATLAB

改进的群体智能算法，简称PSO算法，包括C和matlab两种版本(Improved swarm intelligence algorithm, referred to as PSO algorithm, including two versions of C and matlab)

fonction pour calculer angle

Solving Sylvester equations by the method of the characteristic polynomial

Pegasis protocol for wsn matlab code

说明：  Education matlab Language with c practical examples

Matlab simulation for drawing the BER plot of the LTE turbo code, using either the BCJR algorithm or the fully-parallel algorithm. Copyright (C) 2013 Robert G. Maunder The simulation can be started by running the main.m script. This can be modified to either the BCJR algorithm or the fully-parallel algorithm, as well as to the frame length N. As the simulation proceeds, it will gradually plot the BER that can be achieved using various number of decoding iterations, as selected in main.m. A greater number of decoding iterations will give a lower BER. The script main.m can also be modified to make the BER plots smoother and reach lower BERs, at the cost of making the simulation run slower.

脑电信号特征提取 多尺度方法 经验模态分解 均值粗粒化 移动均值粗粒化(Feature Extraction of EEG Signals Multiscale method Empirical Mode Decomposition Mean coarsening Moving mean coarsening)

说明：  冈萨雷斯全书MATLAB例程，全部代码源(Gonzalez book MATLAB routines, all the source code)

基于matlab的曲线拟合，一种函数的拟合，完整代码(Based on the MATLAB curve fitting based on MATLAB curve fitting)

matlab源代码，是非负矩阵分解工具箱，包含乘法更新，最小二乘约束，投影梯度法等方法(Usage: [W,H] = nmf(X,K,alg,maxiter,speak) W: output matrix H: output matrix X: input matrix K: number of components alg: algorithm to use maxiter: maximum number of iterations speak: print to screen Algorithms: mm: Multiplicative updates method using euclidean distance measure. cjlin: Projected gradient method prob: Probabilistic non-negative matrix factorization. als: Alternating least squares. alsobs: Alternating least squares with optimal brain surgeon. Demonstrations: PET: NMF on a PET dataset Text: NMF used on a three different datasets Email, medical, and CNN. Algorithms mm: Multiplicative update method using euclidean distance measure. Described in Lee and Seung, 2001, Algorithms for Non-negative Matrix Factorization, Advances in Neural Information Processing Systems 13, 556-562. This algorithm is the most commonly used algorithm to solve NMF. cjlin: Alternative non-negative least squares using projected gradients. Author: Chih-Je)