gender

说明：  有关dsp的,有好多子程序,还是不错的,欢迎使用(the dsp, there were a lot subroutine, or good, welcomed the use of)

根据Clarke模型对无线信道进行建模，建立了瑞利信道模型(According to Clarke for modeling wireless channel model, the establishment of Rayleigh channel model)

知识进化多目标领域的一篇经典之作，已被同行广泛认同，相信给大家的学习和研究会带来帮组，欢迎下载！(Knowledge of a field of multi-objective evolutionary classic, has been widely recognized by his peers, I believe for everyone to learn and research will bring help group, welcome to download!)

matlab实现apriori算法源代码(Matlab implementation of Apriori algorithm source code )

LDA 人脸识别中的 makebaisc程序段 希望对毕业设计用的到的同学有用(LDA Face Recognition makebaisc program segment would like to graduate design students used to be useful)

自己用支持向量机编的一个小程序，很好的实现了分类(Their series with support vector machine is a small program achieved very good classification)

Grey Image to Color Image Conversion

matlab语言开发的钟表程序，能够实时显示时间日期等信息(watch matlab language development program, able to display information such as time and date)

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)

说明：  该算法是经典的信噪比估计算法——最大似然估计算法，利用接收信道的先验概率密度函数，ML法能够很好的估计信号的信噪比(The algorithm is a classic signal to noise ratio estimation algorithm- maximum likelihood estimation algorithm, using the a priori receiver channel probability density function, ML method can be a very good signal to noise ratio is estimated)