代码搜索：Matrices

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txt 例1.70.txt

例1.70 function[output，output2]=function—example（input1，input2） % 函数题头 %This is function to exchange two matrices % HI行 %input1，input2 are input variables
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readme

DIRECTORY CONTENTS: File L2Discrepeancies: L2 discrepancies of the Sobol and NX sequence in dimensions 4-20. Files NSXGeneratorRows/Columns: The generator matrices for the NX sequence 9base b=2) i
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m getedgeelements_schur.m

function [Ee,ea] = GetEdgeElements_Schur(Ae,ia,pairs) % Compute the edge element matrices [J. Kraus] via Schur complement. % GetEdgeElements_Schur(Ae,ia,pairs) has input parameters % element matr
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www.eeworm.com/read/343493/11944232

m amari_distance.m

function Perf=amari_distance(Q1,Q2); % AMARI_DISTANCE - distance between two matrices. Beware: it does not verify the axioms % of a distance. It is always between 0 and 1. % Copy
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www.eeworm.com/read/343489/11944541

m callacdc_sym.m

%callacdc_sym (call acdc_sym)- a small demo %showing the way to call acdc_sym (the %symmetric version). %generate the target matrices. %for running with old data set newdata=0. newdata=1; i
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m gradient2.m

function [xx,yy] = grad(a,xax,yax) %GRADIENT Approximate gradient. % [PX,PY] = GRADIENT(Z,DX,DY) returns the numerical partial derivatives % of matrix Z in matrices PX = dZ/dx and PY = dZ/dy. DX and
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m amari_distance.m

function Perf=amari_distance(Q1,Q2); % AMARI_DISTANCE - distance between two matrices. Beware: it does not verify the axioms % of a distance. It is always between 0 and 1. % Copy
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www.eeworm.com/read/339590/12223532

m norm2huff.m

function [zipped,info] = norm2huff(vector) %NORM2HUFF Huffman codification (encoder) % For vectors, NORM2HUFF(X) returns a Huffman coded version of the input vector. % For matrices, X(:) is used
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www.eeworm.com/read/150214/12304748

html mod2sparse.html

Sparse Modulo-2 Matrix Routines Sparse Modulo-2 Matrix Routines This module implements operations on matrices in which the elements are a
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www.eeworm.com/read/250980/12372154

m distance_bhattacharyya.m

function [Bc,Bd] = distance_bhattacharyya(v, P, Q) %[Bc,Bd] = distance_bhattacharyya(v, P, Q) % % INPUTS: % v - difference between two means v = p - q % P, Q - covariance matrices % % OUTPU
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