<em id="ao600"></em>
Atmel MCU Timer design example for all of the user
標簽： example design Atmel Timer
上傳時間： 2016-10-30
上傳用戶：wangzhen1990
Multicast Algorithms for Multi-Channel Wireless Mesh Networks
標簽： Multi-Channel Algorithms Multicast Wireless
上傳時間： 2014-01-12
上傳用戶：as275944189
simulating a convolutional encoder allows the user to input a source code to be encoded and also input the values of the generator polynomials. It outputs the encoded data bits, where 1/n is the code rate
標簽： convolutional simulating encoder encoded
上傳時間： 2013-12-21
上傳用戶：253189838
This GUI can be used by entering nu at the MATLAB command prompt. The user can either select a function (f(x)) of their choice or a statistical distribution probability distribution function to plot over a user defined range. The function s integral can be evaluated over a user defined range by using: The composite trapezium, simpsons and gauss-legendre rules. This is useful for calculating accurate probabilities that one might see in statistical tables.
標簽： can entering command MATLAB
上傳時間： 2016-11-07
上傳用戶：偷心的海盜
Will perform 3D Gaussian quadrature over a user-defined volume. The volume is defined by the user with function definitions entered in the appropriate spaces provided on the GUI. The user can change the number of Gauss points to use. Function inputs need not accept vector args.
標簽： volume user-defined quadrature Gaussian
上傳時間： 2013-12-13
上傳用戶：417313137
RBFMIP is a package for training multi-instance RBF neural networks
標簽： multi-instance networks training package
上傳時間： 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
標簽： package multi-label includes networks
上傳時間： 2013-12-05
上傳用戶：xsnjzljj
CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation
標簽： multi-instance multi-insta adapting learning
上傳時間： 2014-01-14
上傳用戶：manlian
This toolbox contains re-implementations of four different multi-instance learners, i.e. Diverse Density, Citation-kNN, Iterated-discrim APR, and EM-DD. Ensembles of these single multi-instance learners can be built with this toolbox
標簽： i.e. re-implementations multi-instance different
上傳時間： 2013-12-19
上傳用戶：haohaoxuexi
This note introduces the two main user adjustments of a video monitor, BRIGHTNESS and CONTRAST . I explain the effect that these controls have on picture reproduction, and I explain how to set them. This note applies to computer monitors, studio video monitors, and television receivers.
標簽： adjustments BRIGHTNESS introduces CONTRAST
上傳時間： 2016-11-13
上傳用戶：xyipie
