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/140697/13066896
m alg022.m
% FIXED-POINT ALGORITHM 2.2
%
% To find a solution to p = g(p) given an
% initial approximation p0
%
% INPUT: initial approximation p0; tolerance TOL;
% maximum number of iterati
www.eeworm.com/read/140697/13066916
m alg026.m
% STEFFENSEN'S ALGORITHM 2.6
%
% To find a solution to g(x) = x
% given an initial approximation p0:
%
% INPUT: initial approximation p0; tolerance TOL;
% maximum number of ite
www.eeworm.com/read/140697/13067016
m alg023.m
% NEWTON-RAPHSON ALGORITHM 2.3
%
% To find a solution to f(x) = 0 given an
% initial approximation p0:
%
% INPUT: initial approximation p0; tolerance TOL;
% maxi
www.eeworm.com/read/140697/13067099
m alg022.m
% FIXED-POINT ALGORITHM 2.2
%
% To find a solution to p = g(p) given an
% initial approximation p0
%
% INPUT: initial approximation p0; tolerance TOL;
% maximum number of iterati
www.eeworm.com/read/140697/13067119
m alg026.m
% STEFFENSEN'S ALGORITHM 2.6
%
% To find a solution to g(x) = x
% given an initial approximation p0:
%
% INPUT: initial approximation p0; tolerance TOL;
% maximum number of ite
www.eeworm.com/read/318488/13477537
m slicebucky.m
function slicebucky
% SLICEBUCKY - Make a bucky ball approximation for sliceomatic
% Written by Eric Ludlam
% Copyright 2002 The MathWorks Inc
disp('Creating bucky ball app
www.eeworm.com/read/318488/13477538
asv slicebucky.asv
function slicebucky
% SLICEBUCKY - Make a bucky ball approximation for sliceomatic
% Written by Eric Ludlam
% Copyright 2002 The MathWorks Inc
disp('Creating bucky ball app
www.eeworm.com/read/316298/13525671
m fuzzy_appx.m
% a function approximation using fuzzy
% written by: NKN (C) -2006 : wineviruse@yahoo.com
clc
clear all
close all
%
% ** Design a fuzzy system to approximate a function
% the function
www.eeworm.com/read/315751/13536870
m dslab.m
% dslab.m - solves for the TE-mode cutoff wavenumbers in a dielectric slab
%
% Usage: [u,v] = dslab(R,Nit)
% [u,v] = dslab(R) (equivalent to Nit=3)
%
% R = frequency radius = k0*a*N
www.eeworm.com/read/312163/13617499
m contents.m
% Kernel feature extraction.
%
% gda - Generalized Discriminant Analysis.
% greedyappx - Kernel greedy data approximation.
% greedykpca - Greedy kernel PCA.
% kpca - Kernel Principal