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/469580/6931609
txt upload1.txt
ode :
#include
#include
#include
#include
class path
{
int n;
int p[10][10];
int a[10][10];
int c[10][10];
public:
void get();
void pm(
www.eeworm.com/read/469586/6931662
txt 2.txt
#include
#include
#include
using namespace std;
// Floyd's All pairs shortest path algorithm (O (n^3) )
// input is adjacency matrix output is matrix of shortest
www.eeworm.com/read/465477/6938004
txt rfc1432.txt
Network Working Group J. Quarterman
Request for Comments: 1432 MIDS
www.eeworm.com/read/175081/6959329
c clc.c
/*----------------------------------------------------------------------
File : clc.c
Contents: probabilistic and fuzzy cluster comparison
Author : Christian Borgelt
History : 28.05.2006 f
www.eeworm.com/read/343753/6963603
m ttr1.m
function [w1,b1,tr,rq] = ttr1(w1,b1,f1,...
xc,P,T,VA,VAT,TE,TET,TP)
%TTR1 Trains a large feed-forward network containing no hidden layers
%the Gauss-Newton method on a Tikhonov regularized proble
www.eeworm.com/read/469416/6976169
m matprint.m
% MATPRINT - prints a matrix with specified format string
%
% Usage: matprint(a, fmt, fid)
%
% a - Matrix to be printed.
% fmt - C style format string to use for
www.eeworm.com/read/469416/6976334
m conffig.m
function fh=conffig(y, t)
%CONFFIG Display a confusion matrix.
%
% Description
% CONFFIG(Y, T) displays the confusion matrix and classification
% performance for the predictions mat{y} compared
www.eeworm.com/read/469416/6976349
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
% stru
www.eeworm.com/read/469416/6976470
m mlphess.m
function [h, hdata] = mlphess(net, x, t, hdata)
%MLPHESS Evaluate the Hessian matrix for a multi-layer perceptron network.
%
% Description
% H = MLPHESS(NET, X, T) takes an MLP network data struct
www.eeworm.com/read/469123/6977808
m sq_dist.m
% sq_dist - a function to compute a matrix of all pairwise squared distances
% between two sets of vectors, stored in the columns of the two matrices, a
% (of size D by n) and b (of size D by m). If o