IMPORTANT YOU SHOUD LOAD IT DOWN FOR USING
標(biāo)簽： IMPORTANT SHOUD USING DOWN
上傳時(shí)間： 2016-03-11
上傳用戶(hù)：王慶才
程控噴泉程序,用step 7 編寫(xiě)的一個(gè)實(shí)例。對(duì)初學(xué)者有幫助。
上傳時(shí)間： 2016-03-16
上傳用戶(hù)：qb1993225
J2ME: Step by step Presented by developerWorks, your source for great tutorials ibm.com/developerWorks
標(biāo)簽： developerWorks developerW Presented tutorials
上傳時(shí)間： 2016-03-29
上傳用戶(hù)：偷心的海盜
Powerpcb gerber output step by step for newbie using powerpcb,just for your work happy!
標(biāo)簽： step for Powerpcb powerpcb
上傳時(shí)間： 2013-12-26
上傳用戶(hù)：change0329
這是從matlab上down的源文件。上面顯示調(diào)試通過(guò)
標(biāo)簽： matlab down 調(diào)試
上傳時(shí)間： 2016-04-13
上傳用戶(hù)：AbuGe
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
標(biāo)簽： Rauch-Tung-Striebel algorithm smoother which
上傳時(shí)間： 2016-04-15
上傳用戶(hù)：zhenyushaw
mirco step 步進(jìn)電機(jī)驅(qū)動(dòng)參考資料
標(biāo)簽： mirco step 步進(jìn)電機(jī)驅(qū)動(dòng) 參考資料
上傳時(shí)間： 2014-01-07
上傳用戶(hù)：diets
runs Kalman-Bucy filter over observations matrix Z for 1-step prediction onto matrix X (X can = Z) with model order p V = initial covariance of observation sequence noise returns model parameter estimation sequence A, sequence of predicted outcomes y_pred and error matrix Ey (reshaped) for y and Ea for a along with inovation prob P = P(y_t | D_t-1) = evidence
標(biāo)簽： matrix observations Kalman-Bucy prediction
上傳時(shí)間： 2016-04-28
上傳用戶(hù)：huannan88
Computer Networking:A Top Down Approach Featuringthe Internet, 3rd edition. Jim Kurose, Keith Ross Addison-Wesley, July 2004. 高等教育出版社 (影印版)
標(biāo)簽： Featuringthe Networking Computer Approach
上傳時(shí)間： 2014-01-27
上傳用戶(hù)：ls530720646
TMS320C6000 DSP Power-Down Logic and Modes Reference Guide (Rev. B).pdf
標(biāo)簽： Power-Down Reference C6000 Logic
上傳時(shí)間： 2014-12-07
上傳用戶(hù)：woshini123456
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