thinkinjava2English Thinking in Java, 2nd Edition, Release 11 To be published by Prentice-Hall mid-June, 2000 Bruce Eckel, President, MindView, Inc. Planet PDF brings you the Portable Document Format (PDF) version of Thinking in Java (2nd Edition). Planet PDF is the premier PDF-related site on the web. There is news, software, white papers, interviews, product reviews, Web links, code SAMPLES, a forum, and regular articles by many of the most prominent and respected PDF experts in the world. Visit our sites for more detail: http://www.planetpdf.com/ http://www.codecuts.com/ http://www.pdfforum.com/ http://www.pdfstore.com/
標簽： thinkinjava2English Prentice-Hall published Thinking
上傳時間： 2014-01-15
上傳用戶：ANRAN
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
msdn幫助文檔；由于文件太大，分3大部分傳：MSDN2001 part1 和SAMPLES和MSDN。SAMPLES分兩部分，把SAMPLES兩部分放到一個目錄SAMPLES下；MSDN又分幾個部分傳；解壓后放到一個MSDN目錄下
上傳時間： 2016-03-05
上傳用戶：ardager
高效的k-means算法實現，使用了k-d樹與局部搜索等提高k-means算法的執行效率，同時包含示例代碼，用c++代碼實現。 Effecient implementation of k-means algorith, k-d tree and local search strategy are implementd to improve the effeciency, SAMPLES are included to show how to use it. All codes are implemented in C++.
上傳時間： 2016-03-28
上傳用戶：yulg
Probability distribution functions. estimation - (dir) Probability distribution estimation. dsamp - Generates SAMPLES from discrete distribution. erfc2 - Normal cumulative distribution function. gmmsamp - Generates sample from Gaussian mixture model. gsamp - Generates sample from Gaussian distribution. cmeans - C-means (or K-means) clustering algorithm. mahalan - Computes Mahalanobis distance. pdfgauss - Computes probability for Gaussian distribution. pdfgmm - Computes probability for Gaussian mixture model. sigmoid - Evaluates sigmoid function.
標簽： distribution Probability estimation functions
上傳時間： 2016-04-28
上傳用戶：13188549192
The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB language ver. 4.2. The software trains a fuzzy architecture, inspired to Takagi-Sugeno approach, on the basis of a training set of N (single) output-(multi) input SAMPLES. The returned model has the form 1) if input1 is A11 and input 2 is A12 then output =f1(input1,input2) 2) if input1 is A21 and input 2 is A22 then output =f2(input1,input2) 看不懂，據高手說，非常有用。
標簽： identification neuro-fuzzy implemented analysis
上傳時間： 2014-01-12
上傳用戶：zgu489
深圳優龍科技LPC2468開發板，ADS SAMPLES.
上傳時間： 2016-10-15
上傳用戶：tonyshao
The files in this directory comprise ANSI-C language reference implementations of the CCITT (International Telegraph and Telephone Consultative Committee) G.711, G.721 and G.723 voice compressions. They have been tested on Sun SPARCstations and passed 82 out of 84 test vectors published by CCITT (Dec. 20, 1988) for G.721 and G.723. [The two remaining test vectors, which the G.721 decoder implementation for u-law SAMPLES did not pass, may be in error because they are identical to two other vectors for G.723_40.]
標簽： implementations directory reference comprise
上傳時間： 2014-01-22
上傳用戶：Breathe0125
this a SVM toolbox,it is very useful for someone who just learn SVM.In order to be undestood easily,the toolbox also contains some SAMPLES.
標簽： SVM undestood someone toolbox
上傳時間： 2013-12-31
上傳用戶：ztj182002
This Telecommunication Standard [TS] describes the detailed mapping from input blocks of 160 speech SAMPLES in 13-bit uniform PCM format to encoded blocks of 95, 103, 118, 134, 148, 159, 204, and 244 bits and from encoded blocks of 95, 103, 118, 134, 148, 159, 204, and 244 bits to output blocks of 160 reconstructed speech SAMPLES
標簽： Telecommunication describes Standard detailed
上傳時間： 2013-12-12
上傳用戶：cuibaigao
