代码搜索：Matrix
找到约 10,000 项符合「Matrix」的源代码
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www.eeworm.com/read/133946/14016982
m analysis.m
function [E,bE,Nc,mCe,mC,T,U] = analysis(M,D,st,s);
%
% Ph.D. Thesis
% Copyright by Leandro Nunes de Castro
% March, 2000
% Immune Network (iNet) - Description in iNet.doc
% Function determine
www.eeworm.com/read/133944/14017048
m mahaldist.m
function D = mahaldist(X, Y, W)
%MAHALDIST Mahalanobis distance.
%
% D = MAHALDIST(X, Y, W) computes a distance matrix D where the element
% D(i,j) is the Mahalanobis distance between the points X
www.eeworm.com/read/235612/14060221
m event_spike.m
function amat=event_spike(amat,t,x,tnot,xnot,amp)
% EVENT_SPIKE: inserts a spike in a matrix
%
% amat=event_spike(amat,t,x,tnot,xnot,amp)
%
% EVENT_SPIKE inserts a spike event in a matrix.
%
%
www.eeworm.com/read/235612/14060608
m svdsolv.m
function [a,var]= svdsolv(u,s,v,data,vardata)
% solve a linear system given its sigular value decomposition
%
% [a,var] = svdsolv( u, s, v, data, vardata)
% [a,var] = svdsolv( u, s, v, data)
%
% u =
www.eeworm.com/read/235612/14060812
m poly2d.m
function [xgrid,ygrid,zgrid]=poly2d(coeff,order,xcoord,ycoord)
% compute a 2-D polynomial and return gridded values
%
% [xgrid,ygrid,zgrid]=poly2d(coeff,order,xcoord,ycoord)
%
% coeff = a vector of
www.eeworm.com/read/235612/14061553
m contents.m
% The CREWES Migration toolbox
%
% This is a collection of textbook seismic migration routines that has been
% used for instructional purposes. Algorithms include f-k, Kirchhoff, and
% phaseshift migr
www.eeworm.com/read/235612/14061604
m event_spike.m
function amat=event_spike(amat,t,x,tnot,xnot,amp)
% amat=event_spike(amat,t,x,tnot,xnot,amp)
%
% EVENT_SPIKE inserts a spike event in a matrix.
%
% amat ... the matrix of size nrows by ncols
%
www.eeworm.com/read/205039/15327862
m semplicecorr.m
function [delta,dev,cor,C] = semplicecorr(DX,DR,legame)
%SEMPLICECORR correlation between risk factors and assets (normal method).
%
% [delta,dev,cor,C] = semplicecorr(DX,DR,legame) calculates the ve
www.eeworm.com/read/204454/15339378
m empca.m
function [evec,eval] = empca(data,k,iter,Cinit)
%[evec,eval] = empca(data,k,iter,Cinit)
%
% EMPCA
%
% finds the first k principal components of a dataset
% and their associated eigenvales using the E