代码搜索：normalisation
找到约 94 项符合「normalisation」的源代码
代码结果 94
www.eeworm.com/read/416749/2118701
svn-base 10-documents_normalisation.sql.svn-base
ALTER TABLE `documents` DROP COLUMN `document_type_id`; # was int(11) NOT NULL default '0'
ALTER TABLE `documents` DROP COLUMN `size`; # was bigint(20) NOT NULL default '0'
ALTER TABLE `documents` D
www.eeworm.com/read/185152/9054678
m hnorm.m
function coords = hnorm(homcoords)
% DEVELOPMENT PHASE
%
% homogen normalisation: (xu, yu, u) -> (x, y) or (xu, yu, zu, u) -> (x, y, z)
% coords ... n x 3 (coplanar) or n x 4 (3D)
[n m] = size(homcoo
www.eeworm.com/read/144795/5748442
properties numericnormandnomtodecvectortransformer.properties
#NumericNormAndNomToDecVectorTransformer
#Wed Jan 15 11:45:20 CET 2003
normalisation=Range
www.eeworm.com/read/185152/9054740
m createcdlt.m
function [CDLT, lambda] = createCDLT( Fl, b1, b2, u0, v0, T, M )
%DEVELOPMENT PHASE
%
% CDLT = createCDLT( Fl, b1, b2, u0, v0, T, M )
%
% Fl - focal length
% b1, b2 - models the lack of orthogonality
www.eeworm.com/read/486842/6530651
h knn.h
/* Copyright (C) 1997, 1999 Andrew McCallum
Written by: Andrew Kachites McCallum
This file is part of the Bag-Of-Words Library, `libbow'.
This library is free softwa
www.eeworm.com/read/122800/14667798
h knn.h
/* Copyright (C) 1997, 1999 Andrew McCallum
Written by: Andrew Kachites McCallum
This file is part of the Bag-Of-Words Library, `libbow'.
This library is free softwa
www.eeworm.com/read/117859/14902386
txt bugs.txt
---------------------------------------------------------------------------------
bug # 1
Salut les tftoolboxers,
encore un p'tit bug detecte sur TFRBERT
(le sort s'acharne sur tes fonctions, de
www.eeworm.com/read/228006/14403565
wvf haar_deltalp.wvf
% Haar wavelet with the update step disabled
%
% H = (y - x) * (1 / sqrt(2))
% L = x * sqrt(2)
%
% Prediction -> y' = y - x
% Normalisation -> H = y' * (1 / sqrt(2))
% L =
www.eeworm.com/read/228006/14403561
wvf legall_5x3_deltalp.wvf
%LeGall_5x3 with delta low-pass = 1/3 wavelet
%
% H = (-1/2*x(-1) + x(0) - 1/2*x(1)) * (1 / sqrt(2))
% L = x(0) * sqrt(2)
%
% Prediction -> y(0)' = y(0) - 0.5 * (x(-1) + x(1))
% Update
www.eeworm.com/read/431675/8661684
m cnormc.m
%CNORMC Classifier normalisation for good posteriori probabilities
%
% W = cnormc(W,A)
%
% The mapping W is scaled according to the dataset A in such a
% way that A*W*classc represents as good as