hard disk drive servo control tools, it is very helpful
標簽： control helpful drive servo
上傳時間： 2013-12-17
上傳用戶：wangzhen1990
Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
標簽： Intelligence Conference Artificial European
上傳時間： 2015-11-07
上傳用戶：15736969615
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
a program that can lock the hard disk
上傳時間： 2013-12-18
上傳用戶：tianjinfan
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
