代码搜索：multidimensional

找到约 559 项符合「multidimensional」的源代码

代码结果 559
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m normalise.m

function [M, z] = normalise(A, dim) % NORMALISE Make the entries of a (multidimensional) array sum to 1 % [M, c] = normalise(A) % c is the normalizing constant % % [M, c] = normalise(A, dim) % I
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www.eeworm.com/read/396844/2407629

m argmin.m

function indices = argmin(v) % ARGMIN Return as a subscript vector the location of the smallest element of a multidimensional array v. % indices = argmin(v) % % Returns the first minimum in the case o
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www.eeworm.com/read/387667/2557122

cube readme.cube

This directory contains the code for the user-defined type, CUBE, representing multidimensional cubes. FILES ----- Makefile building instructions for the shared library README.cube the file you
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www.eeworm.com/read/372575/2771915

m lms_eq.m

% lms_eq.m - use multidimensional LMS algorithm to estimate channel response % written for MATLAB 4.0 % % Input parameters: % Xi : matrix of training/test points - each row is
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www.eeworm.com/read/349380/8318363

m lms_eq.m

% lms_eq.m - use multidimensional LMS algorithm to estimate channel response % written for MATLAB 4.0 % % Input parameters: % Xi : matrix of training/test points - each row is
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www.eeworm.com/read/147186/12579032

m normalize.m

function [M, z] = normalise(A, dim) % NORMALISE Make the entries of a (multidimensional) array sum to 1 % [M, c] = normalise(A) % c is the normalizing constant % % [M, c] = normalise(A, dim) % I
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www.eeworm.com/read/147186/12579177

m normalise.m

function [M, z] = normalise(A, dim) % NORMALISE Make the entries of a (multidimensional) array sum to 1 % [M, c] = normalise(A) % c is the normalizing constant % % [M, c] = normalise(A, dim) % I
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www.eeworm.com/read/205036/15328931

m a2_sptensor_doc.m

%% Sparse Tensors % MATLAB has no native ability to store sparse multidimensional arrays, % only sparse matrices. Moreover, the compressed sparse column storage % format for MATLAB sparse matrices
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www.eeworm.com/read/288304/8643835

m lms_ar_pred.m

% lms_AR_pred.m - use multidimensional LMS algorithm to predict AR process % written for MATLAB 4.0 % % Input parameters: % Xi : matrix of training/test points - each row is
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www.eeworm.com/read/380466/9146936

m modul.m

function sig_modul = modul(data,md,varargin) %MODUL Multidimensional digital modulator % S = MODUL(Q,MD,'PropertyName',PropertyValue,...) performs linear % memoryless digital modulation of channe
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