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.
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.
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.
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
％ 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
％
//通過(guò)18B20檢測(cè)的數(shù)字溫度可在電腦上顯示當(dāng)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
JAVA music player.
Project Homepage :
http://www.javazoom.net/jlgui/jlgui.html
Developer Homepage :
http://sourceforge.net/project/?group_id=1344
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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.
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).
