GSM TRAINING講述了GSM系統(tǒng)的基本原理，是通信入門項(xiàng)目的很好教材。
上傳時(shí)間： 2014-11-12
上傳用戶：啊颯颯大師的
PowerPCB TRAINING course
標(biāo)簽： PowerPCB TRAINING course
上傳時(shí)間： 2016-07-05
上傳用戶：釣鰲牧馬
* acousticfeatures.m: Matlab script to generate TRAINING and testing files from event timeseries. * afm_mlpatterngen.m: Matlab script to extract feature information from acoustic event timeseries. * extractevents.m: Matlab script to extract event timeseries using the complete run timeseries and the ground truth/label information. * extractfeatures.m: Matlab script to extract feature information from all acoustic and seismic event timeseries for a given run and set of nodes. * sfm_mlpatterngen.m: Matlab script to extract feature information from esmic event timeseries. * ml_train1.m: Matlab script implementation of the Maximum Likelihood TRAINING Module. ?ml_test1.m: Matlab script implementation of the Maximum Likelihood Testing Module. ?knn.m: Matlab script implementation of the k-Nearest Neighbor Classifier Module.
標(biāo)簽： acousticfeatures timeseries generate TRAINING
上傳時(shí)間： 2013-12-26
上傳用戶：牛布牛
matlab TRAINING power point
標(biāo)簽： TRAINING matlab power point
上傳時(shí)間： 2013-12-26
上傳用戶：hn891122
書籍“Regularization tools for TRAINING large feed-forward neural networks using Automatic Differentiation”的源碼文件
標(biāo)簽： Regularization Differentiat feed-forward Automatic
上傳時(shí)間： 2013-11-29
上傳用戶：star_in_rain
gmmTrain: Parameter TRAINING for gaussian mixture model (GMM)
標(biāo)簽： Parameter gmmTrain gaussian TRAINING
上傳時(shí)間： 2014-01-16
上傳用戶：chenbhdt
Altium Designer 6 TRAINING for FPGA,Software andSystemsDevelopmentEmbedded Intelligence TRAINING
標(biāo)簽： TRAINING andSystemsDevelopmentEmbedded Intelligence Designer
上傳時(shí)間： 2013-12-18
上傳用戶：xuanjie
RBFMIP is a package for TRAINING multi-instance RBF neural networks
標(biāo)簽： multi-instance networks TRAINING package
上傳時(shí)間： 2014-01-23
上傳用戶：refent
BPMLL is a package for TRAINING multi-label BP neural networks. The package includes the MATLAB code of the algorithm BP-MLL, which is designed to deal with multi-label learning. It is in particular useful when a real-world object is associated with multiple labels simultaneously
標(biāo)簽： package multi-label includes networks
上傳時(shí)間： 2013-12-05
上傳用戶：xsnjzljj
Sequential Minimal Optimization- A Fast Algorithm for TRAINING Support Vector Machines
標(biāo)簽： Optimization Sequential Algorithm Machines
上傳時(shí)間： 2016-11-25
上傳用戶：youmo81
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