代码搜索:Variance

找到约 2,271 项符合「Variance」的源代码

代码结果 2,271
www.eeworm.com/read/255755/12058001

m klldc.m

%KLLDC Linear classifier built on the KL expansion of the common covariance matrix % % W = KLLDC(A,N) % W = KLLDC(A,ALF) % % INPUT % A Dataset % N Number of significant eigenvectors % AL
www.eeworm.com/read/152646/12095289

c learn.c

/*************************************************************************** File Name : learn.c Purpose : provides routines to learn shape matrix and deformation variance. Release
www.eeworm.com/read/152597/12100112

m mod2trans.m

No=variance; tx_waveform=bpsk(u,1); %amp= 1 rx_waveform=awgn(tx_waveform,No);
www.eeworm.com/read/340968/12116785

mht gran_c.mht

From: Subject: Date: Wed, 27 Sep 2006 22:48:21 +0800 MIME-Version: 1.0 Content-Type: text/html; charset="gb2312" Content-Transfer-Encoding: quoted-printabl
www.eeworm.com/read/340676/12140264

m awgn.m

%************************************************************************************* % This function pertains to the addition of AWGN with mean zero and % parameter 'variance' to
www.eeworm.com/read/152068/12146888

lst 例11-02计算结果.lst

The SAS System 20:55 Wednesday, April 3, 2002 1 Analysis of Variance Procedure Class
www.eeworm.com/read/150905/12249322

m klldc.m

%KLLDC Linear classifier built on the KL expansion of the common covariance matrix % % W = KLLDC(A,N) % W = KLLDC(A,ALF) % % INPUT % A Dataset % N Number of significant eigenvectors % AL
www.eeworm.com/read/150862/12255599

c mrandom.c

#include #include #include #include "msp.h" float randnu(long *iseed) { float z; *iseed=2045*(*iseed)+1; *iseed=*iseed-(*iseed/1048576)*10
www.eeworm.com/read/150861/12255669

c mrandom.c

#include #include #include #include "msp.h" float randnu(long *iseed) { float z; *iseed=2045*(*iseed)+1; *iseed=*iseed-(*iseed/1048576)*10
www.eeworm.com/read/149739/12353597

m klldc.m

%KLLDC Linear classifier built on the KL expansion of the common covariance matrix % % W = KLLDC(A,N) % W = KLLDC(A,ALF) % % INPUT % A Dataset % N Number of significant eigenvectors % AL