This example describes how to use the ADC and DMA to transfer continuously converted data from ADC to a data buffer. The ADC is configured to converts continuously ADC channel14. Each time an end of conversion occurs the DMA transfers, in circular mode, the converted data from ADC1 DR register to the ADC_ConvertedValue VARiable. The ADC1 clock is set to 14 MHz.
標簽： continuously ADC describes converted
上傳時間： 2014-01-03
上傳用戶：徐孺
Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the principal ％ component subspace U of dimension PPCA_DIM using a centred covariance matrix X. The VARiable VAR contains the off-subspace variance (which is assumed to be spherical), while the vector LAMBDA contains the variances of each of the principal components. This is computed using the eigenvalue and eigenvector decomposition of X.
標簽： Probabilistic Components Principal Analysis
上傳時間： 2016-04-28
上傳用戶：qb1993225
Integration的EZMac Plus，對于開發IA4420/4421很有用！ VARiable packet length protocol with packet forwarding capability MAC layer for simplifying EZRadio designs
標簽： Integration EZMac Plus
上傳時間： 2016-05-12
上傳用戶：alan-ee
This demo shows the use of the PWM block in generating the pulse waveform whose duty cycle is changing regularly. The PWM waveform period is VARiable, while the width of the pulse remains constant.
標簽： the generating waveform changi
上傳時間： 2014-01-15
上傳用戶：kr770906
There are two files in the zip folder. bpsk_spread.m and jakesmodel.m Steps for simulation: 1] Run jakesmodel.m first 2] Then run bpsk_spread.m . 3] Note that during the first run bpsk_spread.m has no rayleigh fading.This is because the corresponding code has been commented 4] The resulting performance is stored in BER_awgn. 5] Now uncomment the Rayleigh Fading code in bpsk_spread.m file. 6] Same time comment BER_awgn (line 112) and uncomment BER_ray VARiable. 7] Run the simulation. To compare the perfromances of the receiver using DSSS plot the BER_awgn and BER_ray
標簽： bpsk_spread jakesmodel simulation folder
上傳時間： 2016-05-19
上傳用戶：ynsnjs
％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of VARiable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none) ％ maxiter - maximum number of iteration allowed ([] for none) ％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) ％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) ％ ％ Ouputs: ％ W(1,k) - estimated weights of GM ％ M(d,k) - estimated mean vectors of GM ％ V(d,d,k) - estimated covariance matrices of GM ％ L - log likelihood of estimates ％
標簽： multidimensional estimation algorithm Gaussian
上傳時間： 2013-12-03
上傳用戶：我們的船長
//通過18B20檢測的數字溫度可在電腦上顯示當前溫度值 #include <reg52.h> #define uchar unsigned char #define uint unsigned int sbit DS=P2^2 //define interface uint temp // VARiable of temperature uchar flag1 // sign of the result positive or negative sbit dula=P2^6 sbit wela=P2^7
標簽： define unsigned include 18B20
上傳時間： 2014-01-19
上傳用戶：Andy123456
一個基于Java的小游戲，有助于幫助理解Java中Class之間的數據傳遞以及public, private VARiable的不同用法。
上傳時間： 2016-10-02
上傳用戶：jcljkh
JAVA music player. Project Homepage : http://www.javazoom.net/jlgui/jlgui.html Developer Homepage : http://sourceforge.net/project/?group_id=1344 ----------------------------------------------------- To launch jlGui just doucle click under jlGui2.0.jar. If nothing appear then edit jlGui.bat (or jlGui.sh) script and setup JLGUI_HOME VARiable and launch the script. To play local file : Left click on "Eject" button. To play remote file/stream : Right click on "Eject" Button. To fill in playlist : Edit default.m3u file before launching jlGui.
標簽： jlgui Developer Homepage javazoom
上傳時間： 2016-11-16
上傳用戶：wpwpwlxwlx
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
