代码搜索：Normalized
找到约 4,216 项符合「Normalized」的源代码
代码结果 4,216
www.eeworm.com/read/106690/15626686
m kurt.m
% kurt() - return kurtosis of input data distribution
%
% Usage:
% >> k=kurt(data)
%
% Algorithm:
% Calculates kurtosis or normalized 4th moment of an input data vector
% Given a matrix, returns
www.eeworm.com/read/431675/8661834
m subsm.m
%SUBSM Find subspace map
%
% [W,alf] = subsm(A,n)
%
% A n-dimensional subspace map for the dataset A is found using PCA,
% such that it contains the origin. All object in A are normalized
% first on u
www.eeworm.com/read/386050/8767493
m classc.m
%CLASSC Convert mapping to classifier
%
% W = CLASSC(W)
% W = W*CLASSC
%
% INPUT
% W Any mapping or dataset
%
% OUTPUT
% W Classifier mapping or normalized dataset: outputs/features sum to 1
%
www.eeworm.com/read/283135/9040853
asv mspc.asv
function ms=mspc(x,f)
% The function MSPC calculates a normalized marginal damping spectrum
% of x(k,n), where k specifies the number of frequencies, and
% n is the number of time values.
%
%
www.eeworm.com/read/283135/9040862
m mspc.m
function ms=mspc(x,f)
% The function MSPC calculates a normalized marginal damping spectrum
% of x(k,n), where k specifies the number of frequencies, and
% n is the number of time values.
%
%
www.eeworm.com/read/359212/10161244
m colorseg.m
%COLORSEG Segment a color image.
%
% seg = colorseg(im, map)
%
% Two windows are displayed, one the bivariant histogram in
% normalized (r,g) coordinates, the other the original image.
%
% For each pi
www.eeworm.com/read/273787/10901176
m freqplot.m
% FREQPLOT(B,A,color)
%
% This function is used to plot the amplitude
% response of filter or signal. A logarithmic
% (base 10) scale is used for the Y-axis.
% X-axis is normalized freqency from
www.eeworm.com/read/418695/10935245
m subsm.m
%SUBSM Find subspace map
%
% [W,alf] = subsm(A,n)
%
% A n-dimensional subspace map for the dataset A is found using PCA,
% such that it contains the origin. All object in A are normalized
% first on u
www.eeworm.com/read/271244/11001999
m mspc.m
function ms=mspc(x,f)
% The function MSPC calculates a normalized marginal damping spectrum
% of x(k,n), where k specifies the number of frequencies, and
% n is the number of time values.
%
%
www.eeworm.com/read/299984/7140009
m classc.m
%CLASSC Convert mapping to classifier
%
% W = CLASSC(W)
% W = W*CLASSC
%
% INPUT
% W Any mapping or dataset
%
% OUTPUT
% W Classifier mapping or normalized dataset: outputs/features sum to 1
%