代码搜索：Fitting
找到约 695 项符合「Fitting」的源代码
代码结果 695
www.eeworm.com/read/371970/2777045
java abstractcurvefitting.java
/**
* Description: Curve fitting function
*
* @ Author Create/Modi Note
* Xiaofeng Xie Jun 26, 2008
*
* @version 1.0
* @Since MAOS1.0
*
*/
package problem.custom;
www.eeworm.com/read/371970/2777046
java multiexpcoscurvefitting.java
/**
* Description: Curve fitting function
*
* @ Author Create/Modi Note
* Xiaofeng Xie Jun 26, 2008
*
* @version 1.0
* @Since MAOS1.0
*
*/
package problem.custom;
www.eeworm.com/read/371970/2777047
java padecurvefitting.java
/**
* Description: Pade fitting function
*
* @ Author Create/Modi Note
* Xiaofeng Xie Jun 26, 2008
*
* @version 1.0
* @Since MAOS1.0
*
*/
package problem.custom;
www.eeworm.com/read/371970/2777048
java polynomialcurvefitting.java
/**
* Description: Polynomial fitting function
*
* @ Author Create/Modi Note
* Xiaofeng Xie Jun 26, 2008
*
* @version 1.0
* @Since MAOS1.0
*
*/
package problem.custo
www.eeworm.com/read/366359/2890852
c fitblk.c
/* fitblk.c: example of fitting compressed output to a specified size
Not copyrighted -- provided to the public domain
Version 1.1 25 November 2004 Mark Adler */
/* Version history:
1
www.eeworm.com/read/473927/6824019
txt 2925.txt
Rule:
--
Sid:
2925
--
Summary:
This event is generated when an image fitting the profile of a web bug
has been detected in network traffic.
--
Impact:
Information disclosure.
--
Detailed In
www.eeworm.com/read/147096/12584989
m optdemo.m
% ------- OPTIMIZATION TOOLBOX Demonstrations---
%
% 1) Tutorial Walk Through
% 2) Banana Function
% 3) Goal Attainment
% 4) Data fitting
%
% 0) Quit
echo off
% Optimization Tool
www.eeworm.com/read/101557/15826904
m optdemo.m
% ------- OPTIMIZATION TOOLBOX Demonstrations---
%
% 1) Tutorial Walk Through
% 2) Banana Function
% 3) Goal Attainment
% 4) Data fitting
%
% 0) Quit
echo off
% Optimization Tool
www.eeworm.com/read/100594/15870250
h leastsqu.h
/*NRY 1/90 - The following procedures are interfaces to curve fitting
algorithms which use the Least Square Method. Given a set of data
points and an uncertainty factor for each poin
www.eeworm.com/read/191902/8417257
m local_polynomial.m
function D = Local_Polynomial(features, targets, Nlp, region)
% Classify using the local polynomial fitting
% Inputs:
% features - Train features
% targets - Train targets
% Nlp - Number of t