代码搜索：Difference
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www.eeworm.com/read/441402/7670964
me l_read.me
L_READ.ME
ASCII-file accompanying the MATLAB M-files for the LAMBDA-method
for GPS double difference ambiguity resolution.
Development of the LAMBDA method
--------------------------------
The
www.eeworm.com/read/435208/7795490
m fdtd1d.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Scott Hudson, WSU Tri-Cities
%1D electromagnetic finite-difference time-domain (FDTD) program.
%Assumes Ey and Hz field compone
www.eeworm.com/read/399996/7816935
m cartfunctions.m
function delta = CARTfunctions(split_point, patterns, targets, dim, split_type)
%Calculate the difference in impurity for the CART algorithm
Uc = unique(targets);
for i = 1:length(Uc),
in =
www.eeworm.com/read/434325/7874711
m forwdif.m
function U = forwdif(f,g1,g2,a,b,c,n,m)
%---------------------------------------------------------------------------
%FORWDIF Finite difference solution to the heat equation.
% Sample call
% U
www.eeworm.com/read/198140/7949931
m costfuncmad.m
% Computes the Mean Absolute Difference (MAD) for the given two blocks
% Input
% currentBlk : The block for which we are finding the MAD
% refBlk : the block w.r.t. which the MAD is being
www.eeworm.com/read/198140/7950061
m costfuncmad.m
% Computes the Mean Absolute Difference (MAD) for the given two blocks
% Input
% currentBlk : The block for which we are finding the MAD
% refBlk : the block w.r.t. which the MAD is being
www.eeworm.com/read/397099/8068965
m cartfunctions.m
function delta = CARTfunctions(split_point, patterns, targets, dim, split_type)
%Calculate the difference in impurity for the CART algorithm
Uc = unique(targets);
for i = 1:length(Uc),
in =
www.eeworm.com/read/245941/12771047
m cartfunctions.m
function delta = CARTfunctions(split_point, patterns, targets, dim, split_type)
%Calculate the difference in impurity for the CART algorithm
Uc = unique(targets);
for i = 1:length(Uc),
in =
www.eeworm.com/read/144399/12797272
m fidiff.m
function fidiff(x)
% fidiff First order finite-difference approximation to d/dx of exp(x)
%
% Synopsis: fidiff(x)
%
% Input: x = (optional) value at which the derivative is to be evaluated
www.eeworm.com/read/330850/12865043
m cartfunctions.m
function delta = CARTfunctions(split_point, patterns, targets, dim, split_type)
%Calculate the difference in impurity for the CART algorithm
Uc = unique(targets);
for i = 1:length(Uc),
in =