gmmTrain: Parameter training for gaussian mixture model (GMM)
標簽： Parameter gmmTrain gaussian training
上傳時間： 2014-01-16
上傳用戶：chenbhdt
lcd test_pongball crosshair model
標簽： test_pongball crosshair model lcd
上傳時間： 2016-10-30
上傳用戶：a3318966
cognitive radio model programme with MATLAB
標簽： cognitive programme MATLAB radio
上傳時間： 2014-02-23
上傳用戶：BIBI
Telelogic Tau 面向復雜系統和應用程序的模型驅動開發 Telelogic Tau® 是面向系統及應用程序的分析、設計、開發和測試的Model Driven Development™ 環境，它采用包括Unified Modeling Language™ 2.0 (UML™ )、SysML和Model-Driven Architecture® (MDA® )在內的諸多行業標準。
標簽： Telelogic Development Tau Driven
上傳時間： 2014-01-19
上傳用戶：gaojiao1999
Model Predictive control
標簽： Predictive control Model
上傳時間： 2014-10-11
上傳用戶：電子世界
duo to change channel pos algrithm code you can change this message to me
標簽： change algrithm channel message
上傳時間： 2016-11-12
上傳用戶：AbuGe
*** *** *** *** *** *****/ /* 基于遺傳算法的人工生命模擬 AL_GA.C */ /* An Artificial Life Simulation model Based on Genetic Algorithm */ /* 同濟大學計算機系 王小平 2000年5月
標簽： Artificial Simulation AL_GA model
上傳時間： 2016-11-15
上傳用戶：ls530720646
model OF the OFDM communication in simulink. And I was successful in completing it using a Bernoulli binary generator as the input source (Basic_OFDM.mdl).
標簽： communication completing successful Bernoulli
上傳時間： 2014-01-10
上傳用戶：13188549192
PRINCIPLE: The UVE algorithm detects and eliminates from a PLS model (including from 1 to A components) those variables that do not carry any relevant information to model Y. The criterion used to trace the un-informative variables is the reliability of the regression coefficients: c_j=mean(b_j)/std(b_j), obtained by jackknifing. The cutoff level, below which c_j is considered to be too small, indicating that the variable j should be removed, is estimated using a matrix of random variables.The predictive power of PLS models built on the retained variables only is evaluated over all 1-a dimensions =(yielding RMSECVnew).
標簽： from eliminates PRINCIPLE algorithm
上傳時間： 2016-11-27
上傳用戶：凌云御清風
Inside the C++ Object Model Inside the C++ Object Model focuses on the underlying mechanisms that support object-oriented programming within C++: constructor semantics, temporary generation, support for encapsulation, inheritance, and "the virtuals"-virtual functions and virtual inheritance. This book shows how your understanding the underlying implementation models can help you code more efficiently and with greater confidence. Lippman dispells the misinformation and myths about the overhead and complexity associated with C++, while pointing out areas in which costs and trade offs, sometimes hidden, do exist. He then explains how the various implementation models arose, points out areas in which they are likely to evolve, and why they are what they are. He covers the semantic implications of the C++ object model and how that model affects your programs.
上傳時間： 2013-12-24
上傳用戶：zhouli
