代码搜索：factor
找到约 6,651 项符合「factor」的源代码
代码结果 6,651
www.eeworm.com/read/258201/11877069
txt 6.txt
1: Dev Biol. 2007 Jul 15;307(2):300-13. Epub 2007 May 6.
FGF9 regulates early hypertrophic chondrocyte differentiation and skeletal
vascularization in the developing stylopod.
Hung IH, Yu K, La
www.eeworm.com/read/258201/11877135
txt test.txt
1: J Endocrinol. 2005 Oct;187(1):135-47.
Fibroblast growth factor (FGF) 2 and FGF9 mediate mesenchymal-epithelial
interactions of peritubular and Sertoli cells in the rat testis.
El Ramy R, Ver
www.eeworm.com/read/154843/11923833
m lin2pcma.m
function p=lin2pcma(x,m,s)
%LIN2PCMA Convert linear PCM to A-law P=(X,M,S)
% pcma = lin2pcma(lin) where lin contains a vector
% or matrix of signal values.
% The input values will be converted to
www.eeworm.com/read/342347/12026983
cpp toj_2845.cpp
/*2845. Factorial Time Limit: 1.0 Seconds Memory Limit: 65536K
Total Runs: 387 Accepted Runs: 136
Robby is a clever boy, he can do multiplication very quickly, even in base-2 (binary system),
www.eeworm.com/read/152442/12113209
m gaussianmask.m
function M = gaussianMask(k,s)
% k: the scaling factor
% s: standard variance
R = ceil(3*s); % cutoff radius of the gaussian kernal
for i = -R:R,
for j = -R:R,
M(i+ R+1,j+R+1) =
www.eeworm.com/read/150238/12302961
m lin2pcma.m
function p=lin2pcma(x,m,s)
%LIN2PCMA Convert linear PCM to A-law P=(X,M,S)
% pcma = lin2pcma(lin) where lin contains a vector
% or matrix of signal values.
% The input values will be converted to
www.eeworm.com/read/336521/12439808
m lin2pcma.m
function p=lin2pcma(x,m,s)
%LIN2PCMA Convert linear PCM to A-law P=(X,M,S)
% pcma = lin2pcma(lin) where lin contains a vector
% or matrix of signal values.
% The input values will be converted to
www.eeworm.com/read/234502/14110984
m gaussianmask.m
function M = gaussianMask(k,s)
% k: the scaling factor
% s: standard variance
R = ceil(3*s); % cutoff radius of the gaussian kernal
for i = -R:R,
for j = -R:R,
M(i+ R+1,j+R+1) =
www.eeworm.com/read/233762/14137596
readme
This code supplies a Java implementation for Relational Markov Networks with discrete potentials. It is being released for educational and research purposes only under the GNU General Public License