资源列表
xuexilicheng
- 有关人工神经网络学习过程中的一些心得和体会，分为第一部分和第二部分，初学者可用！-The artificial neural network learning process in a number of ideas and experience, is divided into Part I and Part II, beginners are available!
qiangdaqi
- ⑴ 设计一个可供8人进行的抢答器。 ⑵ 主持人设置一个控制开关，用来控制系统得清零（显示数码灭）和抢答开始。并设置复位按钮，按动后，重新开始抢答。 ⑶ 抢答器开始时数码管显示序号0，选手抢答实行优先锁存，优先抢答选手的编号一直保持到主持人将系统清除为止。抢答后显示优先抢答者序号，并且不出现其他抢答者的序号。 ⑷ 抢答器具有定时抢答的功能，由主持人预先设定时间。 ⑸ 主持人按下复位开关，使得抢答器再次进入禁止状态，选手编号的LED数字显示器灯熄灭，电路进入原来的初始状态，准备进入下
psoppt
- PSO算法的经典PPT，初学者有很大好处-PSO algorithm is a classic PPT, of great benefit to beginners
Frm8
- Fix for SetEnrollmentData returning ¡ °ERR_INVALID_PARAM¡ ± Programming samples with sample function arguments to verify performance of these three functions: SetEnrollDataStr SetUserTmp, SetUserTmpStr-Fix for SetEnrollmentData
Bayesianclassfier
- 很好的分类算法，大家可以参考一下，我最近在研究它-A good classification algorithm, we can refer to something, I study it recently
ADDC
- ADDc算法，模式识别算法，这是一个函数，打击可以去研究一下啊-ADDc algorithm, pattern recognition algorithm, which is a function, combat can go to look at ah
calculate
- 聚类算法，杜达书上配套的源代码，大家可以研究研究，现在很热门的呢-Clustering algorithms, duda, matching the book s source code，We can research studies,it is now very popular
code
- 这是关于属性约简算法的实现以及改进，traditional是原算法实现，其余代码的是改进；都有详细的注释-This code is about implement and polish of algorithm of attribute reduction,title with traditional is implement of original algorithm,the other are the improvement.They are all commited in detail.
lvq.m
- 基于矢量向量的神经网络图像边缘检测,有消噪的效果，是图像处理的不错程序-baseed on LVQ net work
svm-phasestateofcloudclassificationalgorithmsource
- 利用支持向量机的分类特性，结合modis的云图像，对云相态进行分类，利用svm云相态分类算法源代码-The use of support vector machine classification of features, combined with clouds modis images of the cloud phase state classification using svm-phase state of cloud classification algorithm source c
INFORMATION_THEORETIC_LEARNING
- 模式识别方面的文章，基于瑞利熵的机器学习方法，以及应用举例，建议做MMI的同志学习。-Pattern Recognition in the article, based on Rayleigh entropy machine learning methods, and application examples, it is recommended to do MMI comrades to learn.