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给出纠错码性能测试仿真的一般方法，重点研究其信道差错序列的产生，然后利用Matlab实现卷积码编码及其Viterbi译码的性能测试仿真(Error-correcting codes are given the general simulation performance test methods, focus on the channel error sequence generated, and then the realization of convolutional codes using Matlab coding and Viterbi decoding performance test simulation)

说明：  libsvm用于matlab环境下，简小易用，速度非常快。(libsvm for matlab environment, simple small easy to use, very fast.)

matlab数学手册，矩阵及其基本运算、数值计算与数据分析、符号运算、概率统计、优化问题、模糊逻辑、绘图与图形处理(matlab Math Handbook)

本人搭建的Matlab风电模型、直驱2MW的，研究塔架振动的(I set up the Matlab, 2 mw direct-drive wind model, the mode of vibration，PMSG)

本程序是对V-BLAST系统及其检测算法的仿真，可采用BPSK,QPSK,16QAM,64QAM调制。检测算法为ML，MMSE,ZF,以及采用迫零的连续干扰消除检测算法。(This procedure is the V-BLAST system and its detection algorithm simulation, can be used BPSK, QPSK, 16QAM, 64QAM modulation. Detection Algorithm for the ML, MMSE, ZF, and the use of zero-forcing successive interference cancellation algorithm.)

MATLAB中一些常用的函数，在做实验时可以直接选定函数进行编程。(Some commonly used functions in MATLAB, the experiment can be programmed directly to the selected function.)

chen分数阶的吸引子仿真，很容易实现的，希望可以帮助你。一起学习混沌吧。(chen fractional attractor simulation, it is easy to achieve, I hope you can help. With learning chaos.)

Express gatool use of MATLAB in the implementation of training neural network genetic algorithm procedure

它试图解决的问题，薄弱的标签是一个多学习一种新标签的问题，其中只有部分标签集与每个提供相关培训的例子(This package includes the MATLAB code of the multi-label learning algorithm WELL. It tries to deal with weak label problem which is a new kind of multi-label learning problem, where only a partial label set associated with each training example is provided. A Readme file and an example file are included in the package)

该matlab代码实现了“综合多分支分裂式层次化聚类” (Matlab implementation of Omnibus Multi-Branching Divisive Hierarchical Clustering (OMBDHC) “A competitive omnibus performance criterion for divisive multi-branching hierarchical clustering” by Soeria-Atmadja et al. (submitted). Note that OMB-DHC package is implemented in Matlab code and therefore demands the Matlab core program, as well as the Statistics toolbox of Matlab. Divisive hierarchical clustering (DHC) has emerged as a promising alternative for the identification of sub-structures in multivariate data. Of particular interest is multi-branching DHC, which allows flexible numbers of subclusters at each hierarchical level. One poorly explored issue in multi-branching DHC concerns the actual importance of the two performance criteria (and their associated algorithms) to automatically create clusters and select number of clusters, respectively. Another interesting but hitherto unexplored issue is the possibility to employ a single omnibus performance criterion that guide)