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/154209/11983199
m pyulear.m
function varargout = pyulear( xR, p, nfft, Fs, flag )
%PYULEAR Power Spectrum estimate via Yule-Walker AR method.
% Pxx = PYULEAR(X,ORDER,NFFT) is the Power Spectral Density estimate of
% sig
www.eeworm.com/read/154209/11983356
m pmusic.m
function varargout = pmusic( xR, thresh, varargin )
%PMUSIC Power Spectrum estimate via MUSIC eigenvector method.
% Pxx = PMUSIC(X,P,NFFT) is the Power Spectral Density (PSD) estimate of
% si
www.eeworm.com/read/154124/11988632
m varimax4m.m
% Varimax4M - Varimax rotation as described by Harman (1967, pp. 304-308)
% and implemented by BMDP-4M (Dixon, 1992, pp. 602-603),
% using the simplicity criterion G instead of
www.eeworm.com/read/256506/11993839
m createdistmat.m
function distMat = createDistMat (proj, metric)
%
% PROTOTYPE
% function distMat = createDistMat (proj, metric)
%
% USAGE EXAMPLE(S)
% pcaDistMatCos = createDistMat(pcaProj, 'COS');
%
% GENER
www.eeworm.com/read/153969/11997423
m netgrad.m
function g = netgrad(w, net, x, t)
%NETGRAD Evaluate network error gradient for generic optimizers
%
% Description
%
% G = NETGRAD(W, NET, X, T) takes a weight vector W and a network data
% structure
www.eeworm.com/read/342786/11998953
3 libdmtx.3
.\" $Id: libdmtx.3,v 1.4 2006/10/15 22:08:14 mblaughton Exp $
.\"
.\" Man page for the libdmtx project.
.\"
.\" $ groff -man -T ascii libdmtx.3
.\"
.TH LIBDMTX 3 "October 15, 2006"
.SH NAME
libdmtx \-
www.eeworm.com/read/256389/12002266
java pnt.java
/*
* Copyright (c) 2005 by L. Paul Chew.
*
* Permission is hereby granted, without written agreement and without
* license or royalty fees, to use, copy, modify, and distribute this
* softw
www.eeworm.com/read/153823/12004279
m trineighbors.m
function N = trineighbors(t,T)
%TRINEIGHBORS Find neighbors of a triangle.
% N = trineighbors(t,T)
% t = m-element vector of triangle indices
% T = n x 3 matrix of node indices, where
www.eeworm.com/read/342441/12019671
m emd_mex.m
%EMD (Earth Movers Distance)
% e=emd(w1,w2,C)
% [e,F]=emd(w1,w2,C)
% w1 is the weight vector of the first signature (1 by n1)
% w2 is the weight vector of the second signature (1 by
www.eeworm.com/read/342323/12027725
m user_alg5.m
function [H,S,D]=acsobiro(X,n,p),
% Program implemented and improved by A. Cichocki
% on basis of the classical SOBI algorithm of Belouchrani.
% Attention for noisy data you should take at least