代码搜索：normalisation

找到约 94 项符合「normalisation」的源代码

代码结果 94
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java normalisationexception.java

/* Generated by Together */ package it.itc.ectrl.normkit.common; /** * Parent exception for all exceptions thrown by Normalisation Toolkit * * @author Oliver Fodor (fodor@itc.it) */ pub
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m normalise.m

function [ndata,refval] = normalise(data,type,val) % [ndata,refval] = normalise(data,type,val) % %NORMALISE Normalises a data sequence. % Normalisation type maybe with respect to % varia
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m normalise.m

function [ndata,refval] = normalise(data,type,val) % [ndata,refval] = normalise(data,type,val) % %NORMALISE Normalises a data sequence. % Normalisation type maybe with respect to % varia
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m createiristemplate.m

function [t, m] = createiristemplate(eyeimage_filename) % path for writing diagnostic images global DIAGPATH DIAGPATH = 'diagnostics'; %normalisation parameters radial_res = 64; angular_res =2
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java cnovocabulary.java

package it.itc.ectrl.normkit.common; /** * Vocabulary for crating and parsing Normalisation Map RDF model. * @author Oliver Fodor (fodor@itc.it) */ public class CNOVocabulary { public fina
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changelog

dialog normalisation -------------------- dialnorm results in an nomalized output of -31 dbFS in Line Mode (see [1] 3.61.) For 2-channel output (A52_STEREO and A52_DOLBY) this is lowered by additiona
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java normalisationheuristic.java

package it.itc.ectrl.normkit.cnorm.heuristics; import oracle.xml.parser.schema.*; import it.itc.ectrl.normkit.cnorm.impl.C_NormalisationImpl; /** * Parent class for all normalisation heuris
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java cnoerrors.java

package it.itc.ectrl.normkit.common; /** * Error messages for Conceptual Normalisation. Under Construction. * @author Nuno Silva * @author Oliver Fodor (fodor@itc.it) */ public clas
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m modi_set.m

function f = modi_set(set,mod) % f = modi_set(set,mod) % % Modification of a fuzzy set, or a library of fuzzy sets. % 'mod' : % % 'nor' normalisation. Division of all elements by the maximum membe
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wvf haar.wvf

% Haar wavelet % % H = (y - x) * (1 / sqrt(2)) % L = (x + y) * (1 / sqrt(2)) % % Prediction -> y' = y - x % Update -> x' = x + 0.5 * y' = (x + y)/2 % Normalisation -> H = y' *
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