canny

Multi-Carrier Digital Communications Theory and Applications of OFDM Second Edition Multi-carrier modulation‚ Orthogonal Frequency Division Multiplexing (OFDM) particularly‚ has been successfully applied to a wide variety of digital communications applications over the past several years. Although OFDM has been chosen as the physical layer standard for a diversity of important systems‚ the theory‚ algorithms‚ and implementation techniques remain subjects of current interest. This is clear from the high volume of papers appearing in technical journals and conferences. Multi-carrier modulation continues to evolve rapidly. It is hoped that this book will remain a valuable summary of the technology‚ providing an understanding of new advances as well as the present core technology.

说明：  旅行商问题，起点与终点为同一点，求最短路径，(MTSPF_GA Fixed Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA))

好用的matlab实现凸优化工具包，适用于压缩感知重构过程(Easy to use matlab to achieve a convex optimization tool kit for compressed sensing reconstruction process)

Turbo码编码译码器的研究及其MATLAB实现.(TUrbo)

经典的汉密尔顿回路算法，以Matlab代码编写。(Hamilton classic loop algorithm to Matlab coding.)

法国人应用经验模态分析的方法，各种列子与仿真(The French application experience modal analysis method, and simulation of various Liezi)

simple problem average filter

ILI9225G屏资料,关于寄存器的具体使用方法，以及相关的说明。(ILI9225G screen information about the specific use of registers, and related instructions.)

Induction machine power 50 kw in matlab simulink work on

不错的GM_EM代码。用于聚类分析等方面。( GM_EM- fit a Gaussian mixture model to N points located in n-dimensional space. Note: This function requires the Statistical Toolbox and, if you wish to plot (for k = 2), the function error_ellipse Elementary usage: GM_EM(X,k)- fit a GMM to X, where X is N x n and k is the number of clusters. Algorithm follows steps outlined in Bishop (2009) Pattern Recognition and Machine Learning , Chapter 9. Additional inputs: bn_noise- allow for uniform background noise term ( T or F , default T ). If T , relevant classification uses the (k+1)th cluster reps- number of repetitions with different initial conditions (default = 10). Note: only the best fit (in a likelihood sense) is returned. max_iters- maximum iteration number for EM algorithm (default = 100) tol- tolerance value (default = 0.01) Outputs idx- classification/labelling of data in X mu- GM centres)