机器人的行为控制模拟程序。用于机器人的环境识别。A robot action decision simulation used for robot enviroment recognition.
标签： robot recognition enviroment simulation
上传时间： 2014-08-17
上传用户：ryb
COM versus CORBAA Decision Framework！一本介绍应该使用COM还是CORBA的记录文摘！
标签： COM Framework Decision versus
上传时间： 2013-12-03
上传用户：变形金刚
《Grid Computing: Making the Global Infrastructure a Reality》 由 Fran Berman、Geoffrey Fox 和 Tony Hey 共同编辑的这本书，由 Wiley 于 2003 年 3 月出版。这本大部头的书共 1000 多页，它包含了从各种科学与技术角度研究网格计算的文章和评论，其中包括：网格的历史、语义网格、网格体系结构的概述、网格部署模型、OGSA 和对等网格数据库等许多内容。
标签： Infrastructure Computing Geoffrey Reality
上传时间： 2015-11-12
上传用户：heart520beat
ID3决策树内容简介： 概述 预备知识 决策树生成(Building Decision Tree) 决策树剪枝(Pruning Decision Tree) 捕捉变化数据的挖掘方法 小结
标签： Decision Tree Building Pruning
上传时间： 2013-12-12
上传用户：上善若水
Decision Tree Decision Tr
上传时间： 2013-12-24
上传用户：jing911003
Convolutional(2,1,6) Encoder and soft decision Viterbi Decoder
标签： Convolutional decision Encoder Decoder
上传时间： 2014-01-01
上传用户：cc1
Convolutional(2,1,6) Encoder and soft decision Viterbi Decoder 刚才上载的有错误,已修正
标签： Convolutional decision Encoder Decoder
上传时间： 2016-01-14
上传用户：hoperingcong
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
标签： the decision clusters Cluster
上传时间： 2013-12-21
上传用户：gxmm
主要是KNN（the k-nearest neighbor algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface mapping）算法。 and a simple clustering algorithm.
标签： quantization k-nearest algorithm decision
上传时间： 2016-02-07
上传用户：zhyiroy
A general decision rule for stochastic blind maximum-likelihood OSTBC detection is derived.
标签： maximum-likelihood stochastic detection decision
上传时间： 2013-12-04
上传用户：xcy122677
