代码搜索：Matrix
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html 348-351.html
The Data Compression Book-:Lossy Graphics Compression
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m izigzag.m
% Inverse zigzag scan of a matrix
% Arguments are: a 1-by-m*n array,
% where m & n are vertical & horizontal sizes of an output matrix.
% Function returns a two-dimensional matrix of defined sizes
www.eeworm.com/read/486146/6543948
m izigzag.m
% Inverse zigzag scan of a matrix
% Arguments are: a 1-by-m*n array,
% where m & n are vertical & horizontal sizes of an output matrix.
% Function returns a two-dimensional matrix of defined sizes
www.eeworm.com/read/485544/6552646
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 with
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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
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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 structure
www.eeworm.com/read/485103/6564354
m ntimes.m
function product = ntimes(X,Y,modeX,modeY);
%NTIMES Array multiplication
%
% X*Y is the array/matrix product of X and Y. These are multiplied across the
% modeX mode/dimension of X and modeY
www.eeworm.com/read/485150/6566165
m doubleint_tilingqit.m
function out = doubleint_tilingqit(cfg)
% Custom tiling Q-iteration for the double integrator
% Also includes attempts at tiling Q-i versions different from averaging projection,
% e.g. gradient-l
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inl linearequation.inl
//LinearEquation.inl 线性方程(组)求解函数(方法)定义
// Ver 1.0.0.0
// 版权所有(C) 何渝, 2002
// 最后修改: 2002.5.31
#ifndef _LINEAREQUATION_INL
#define _LINEAREQUATION_INL
//全选主元高斯消去法
template
int L