代码搜索：sprintf
找到约 7,065 项符合「sprintf」的源代码
代码结果 7,065
www.eeworm.com/read/398339/7993171
bak inetserverdlg.cpp.bak
// InetServerDlg.cpp : implementation file
//
//This is InetServ. :-)
//Under development by Bruce Peresky (1999/2000) Origional
//Design by Thomas Kuiper
//MAPI support by Mohamed Yasin
//D
www.eeworm.com/read/398339/7993184
cpp inetserverdlg.cpp
// InetServerDlg.cpp : implementation file
//
//This is InetServ. :-)
//Under development by Bruce Peresky (1999/2000)
//Origional Design by Thomas Kuiper
//MAPI support by Mohamed Yasin
//D
www.eeworm.com/read/297340/8028974
cc cmu-trace.cc
/* -*- Mode:C++; c-basic-offset:8; tab-width:8; indent-tabs-mode:t -*- */
/* Modified and extended by Pablo Martin and Paula Ballester,
* Strathclyde University, Glasgow.
* June, 2003.
*/
/* Copyr
www.eeworm.com/read/297325/8030098
m saveinr.m
%SAVEINR Write an INRIMAGE format file
%
% SAVEINR(filename, im)
%
% Saves the specified image array in a INRIA image format file.
%
% SEE ALSO: loadinr
%
% Copyright (c) Peter Corke, 1999 Ma
www.eeworm.com/read/196840/8055055
m sleepdemo.m
% A demonstration of the HMM software using a Gaussian observation
% model on AR features extracted from an overnight sleep EEG recording.
clear
disp(sprintf(['A demonstration of the HMM software usi
www.eeworm.com/read/196832/8055383
m sleepdemo.m
% A demonstration of the CHMM software using a Gaussian observation
% model on AR features
clear all
disp(sprintf(['A demonstration of the CHMM software using a Gaussian' ...
' observation mode
www.eeworm.com/read/397106/8067803
m pnn_vc.m
% Learns classifier and classifies test set
% using a Probabilistic Neural Network
% Usage
% [trainError, testError, estTrainLabels, estTestLabels] = ...
% PNN_VC(trainFeatures, trainLa
www.eeworm.com/read/295984/8130020
m sor.m
%Successive Over Relaxation迭代程序
function [x,sp]=sor(a,b,n,x1,w)
%误差
e=ones(n,1);
%迭代的解向量
x2=zeros(n,1);
%迭代的次数
k=0;
%当误差没有满足要求时继续迭代
while norm(e,2)>1e-6
%每隔5步显示迭代结果
if (rem(k,5)==0)
www.eeworm.com/read/295984/8130090
m jac.m
%Jacobian迭代程序
function [x,sp]=jac(a,b,n,x1)
%误差
e=ones(n,1);
%迭代的解向量
x2=zeros(n,1);
%迭代的次数
k=0;
%当误差没有满足要求时继续迭代
while norm(e,2)>1e-6
%每隔5步显示迭代结果
if (rem(k,5)==0)
str=sprintf('X
www.eeworm.com/read/333698/12664432
m main.m
clear all
traindata = cell(1,10);
for i=0:9
temp = cell(1,3);%3疙 切嚼
for j=1:3
fname = sprintf('%d%da.wav',i,j);
x = wavread(fname);
temp{1,j}=x';
end
traindata