代码搜索：Approximation
找到约 1,542 项符合「Approximation」的源代码
代码结果 1,542
www.eeworm.com/read/317375/13505361
m fixpt.m
function [k,p,err,P]=fixpt(g,p0,tol,max1)
%Input-g is the iteration function input as a string 'g'
% -p0 is the initial guess for the fixed point
% -tol is the tolerance
% -max1 is the
www.eeworm.com/read/305390/13772321
m seidel.m
function [P,iter]= seidel(G,P,delta, max1)
%Input - G is the nonlinear fixed-point system
% saved as an M-file function
% - P is the initial guess at the solution
%
www.eeworm.com/read/131315/5931421
c erf.c
/*-
* Copyright (c) 1992, 1993
* The Regents of the University of California. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are perm
www.eeworm.com/read/119864/6081770
c powf.c
/* powf.c
*
* Power function
*
*
*
* SYNOPSIS:
*
* float x, y, z, powf();
*
* z = powf( x, y );
*
*
*
* DESCRIPTION:
*
* Computes x raised to the yth power. Analytically,
*
*
www.eeworm.com/read/490637/6450487
m romberg.m
function R = romberg(f, a, b, n)
format long
% ROMBERG -- Compute Romberg table integral approximation.
%
% SYNOPSIS:
% R = romberg(f, a, b, n)
%
% DESCRIPTION:
% Computes the complete
www.eeworm.com/read/480837/6662439
m fixed_point.m
function fixed_point(p0, N)
%Fixed_Point(p0, N) approximates the root of the equation f(x) = 0
%rewritten in the form x = g(x), starting with an initial approximation p0.
%The iterative techniqu
www.eeworm.com/read/410134/11301048
m wtlsini.m
function [r,p,M,dh] = wtlsini(d,w,m)
% WTLSINI - Initial approximation for the WTLS problem.
%
% [r,p,M,dh] = wtlsini(d,w,m)
%
% D = [d1 ... dN] - data matrix, sd := size(D,1)
% W - sd x N weight matr
www.eeworm.com/read/410134/11301115
tex wtls_manual_coverpage.tex
% ?? -> report #
\newcommand{\matlab}{{\sc Matlab}}
\documentclass[11pt,titlepage]{article}
\setlength{\footnotesep}{7mm}
\title{ \ \vspace{-8cm} \\
{\Large\bf \
Katholieke
www.eeworm.com/read/410134/11301123
m tls.m
function [r,p,M,dh] = tls(d,m)
% TLS - Total Least Squares approximation.
%
% [r,p,M,dh] = tls(d,m)
%
% D = [d1 ... dN] - data matrix
% m - complexity specification, m < size(D,1)
% R - parameter of
www.eeworm.com/read/409626/11317610
m nr.m
function [r, niter] = NR(f, J, x0, tol, rerror, maxiter)
% Zero r of the nonlinear system of equations f(x) = 0.
% Here J is the Jacobian matrix of f and x0 is the initial
% approximation of t