代码搜索:Calculation

找到约 2,005 项符合「Calculation」的源代码

代码结果 2,005
www.eeworm.com/read/350718/7149673

h calc.h

/************************************************************************* Calculation function key code define *************************************************************************/
www.eeworm.com/read/333209/7154822

m ut_mweights.m

%UT_MWEIGHTS - Generate matrix form unscented transformation weights % % Syntax: % [WM,W,c] = ut_mweights(n,alpha,beta,kappa) % % In: % n - Dimensionality of random variable % alpha - Transf
www.eeworm.com/read/463435/7181050

c choose.c

/*---------------------------------------------------------------------- File : choose.c Contents: compute n choose k Author : Christian Borgelt History : 29.04.1996 file created
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m qh1.m

function imeval clear; % imdesign.m contains dimension, winding, & rating data krc=2; % 1=copper; 2=aluminum % Winding data VL=540; f=60; p=6; m=3; HP=50; S1=54; S2=51; Cs=8; pitch=8; a=1; % Co
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txt 17-2-e.txt

var head,foot:integer; procedure calculation(var head,foot:integer); var n,cock,rabbit:integer; begin n:=0; for cock:=1 to head do begin rabbit:=head-cock; if cock*
www.eeworm.com/read/453717/7413901

java inputneuron.java

/* * InputNeuron.java * * Created on 2007年11月15日, 上午7:24 * */ package neuralNetwork; /** * input adapter neuron. This kind of neuron never do any calculation just transfer input data
www.eeworm.com/read/451398/7466034

pas wucrc32.pas

{*******************************************************************} { CRC32 calculation of file } { for Delphi 3.0,4.0,5.0,6.0 - C++Builder 3,4,5
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m test_bayes3.m

% PURPOSE: A comparison of Bayesian and ML estimates % using a small dataset %--------------------------------------------------- % USAGE: test_bayes %-------------------
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m compare_models2.m

% PURPOSE: An example of using sar_g() sem_g() Gibbs sampling % spatial model comparisons using log marginal posterior % (on a small data set) %-----------------
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m sar_d3.m

% PURPOSE: An example of using sar on a large data set % Gibbs sampling spatial autoregressive model %--------------------------------------------------- % USAG