機器人的行為控制模擬程序。用于機器人的環境識別。A robot action decision simulation used for robot enviroment recognition.
標簽： robot recognition enviroment simulation
上傳時間： 2014-08-17
上傳用戶：ryb
COM versus CORBAA Decision Framework！一本介紹應該使用COM還是CORBA的記錄文摘！
標簽： COM Framework Decision versus
上傳時間： 2013-12-03
上傳用戶：變形金剛
《Grid Computing: Making the Global Infrastructure a Reality》 由 Fran Berman、Geoffrey Fox 和 Tony Hey 共同編輯的這本書，由 Wiley 于 2003 年 3 月出版。這本大部頭的書共 1000 多頁，它包含了從各種科學與技術角度研究網格計算的文章和評論，其中包括：網格的歷史、語義網格、網格體系結構的概述、網格部署模型、OGSA 和對等網格數據庫等許多內容。
標簽： Infrastructure Computing Geoffrey Reality
上傳時間： 2015-11-12
上傳用戶：heart520beat
ID3決策樹內容簡介： 概述 預備知識 決策樹生成(Building Decision Tree) 決策樹剪枝(Pruning Decision Tree) 捕捉變化數據的挖掘方法 小結
標簽： Decision Tree Building Pruning
上傳時間： 2013-12-12
上傳用戶：上善若水
Decision Tree Decision Tr
上傳時間： 2013-12-24
上傳用戶：jing911003
Convolutional(2,1,6) Encoder and soft decision Viterbi Decoder
標簽： Convolutional decision Encoder Decoder
上傳時間： 2014-01-01
上傳用戶：cc1
Convolutional(2,1,6) Encoder and soft decision Viterbi Decoder 剛才上載的有錯誤,已修正
標簽： Convolutional decision Encoder Decoder
上傳時間： 2016-01-14
上傳用戶：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.
標簽： the decision clusters Cluster
上傳時間： 2013-12-21
上傳用戶：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.
標簽： quantization k-nearest algorithm decision
上傳時間： 2016-02-07
上傳用戶：zhyiroy
A general decision rule for stochastic blind maximum-likelihood OSTBC detection is derived.
標簽： maximum-likelihood stochastic detection decision
上傳時間： 2013-12-04
上傳用戶：xcy122677
