代码搜索：solves
找到约 1,488 项符合「solves」的源代码
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www.eeworm.com/read/204766/15333844
h pr_loqo.h
/*
* File: pr_loqo.h
* Purpose: solves quadratic programming problem for pattern recognition
* for support vectors
*
* Author: Alex J. Smola
* Created: 10/14/97
www.eeworm.com/read/204766/15333857
c pr_loqo.c
/*
* File: pr_loqo.c
* Purpose: solves quadratic programming problem for pattern recognition
* for support vectors
*
* Author: Alex J. Smola
* Created: 10/14/97
www.eeworm.com/read/424063/10501698
m leastsq.m
function [x,OPTIONS,f,JOCOB] = leastsq(FUN,x,OPTIONS,GRADFUN,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10)
%LEASTSQ Solves non-linear least squares problems.
% LEASTSQ solves problems of the form:
% min sum {F
www.eeworm.com/read/147096/12585030
m leastsq.m
function [x,OPTIONS,f,JOCOB] = leastsq(FUN,x,OPTIONS,GRADFUN,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10)
%LEASTSQ Solves non-linear least squares problems.
% LEASTSQ solves problems of the form:
% min sum {F
www.eeworm.com/read/101557/15826920
m leastsq.m
function [x,OPTIONS,f,JOCOB] = leastsq(FUN,x,OPTIONS,GRADFUN,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10)
%LEASTSQ Solves non-linear least squares problems.
% LEASTSQ solves problems of the form:
% min sum {F
www.eeworm.com/read/388785/8575549
m tdofss_eig.m
echo off
% tdofss_eig.m eigenvalue problem solution for tdof undamped model
% Solves for the eigenvalues and eigenvectors in the state space
% form of the tdof system.
clear all;
% define
www.eeworm.com/read/427233/8959632
m as.m
% AS.m
%This program solves Quadratic Programming by using Active Set algorithm.
%n=input('Enter the dimension number of the variable: n= ')
%ME=input('Enter the number of the equality constrain
www.eeworm.com/read/376249/9323432
c hanoi.c
/*
* Towers of Hanoi
*
* This program solves the "Towers of Hanoi" problem, which is to move a stack
* of different sized rings from one of three towers to another. Only one ring
* may be mo
www.eeworm.com/read/178061/9420881
m unimodal.m
function B=unimodal(X,Y,Bold)
%UNIMODAL unimodal regression
%
% Solves the problem min|Y-XB'| subject to the columns of
% B are unimodal and nonnegative. The algorithm is iterative
% If an est
www.eeworm.com/read/358861/10177732
m clsq.m
function [c, n] = clsq (A, dim);
%CLSQ Special constrained least squares
%
% [c, n] = clsq (A, dim) solves the constrained
% least squares Problem
% A (c n)' == 0 subject t