-
Just what is a regular expression, anyway?
Take the tutorial to get the long answer. The short answer is that a regular expression
is a compact way of describing complex patterns in texts. You can use them to search
for patterns and, once found, to modify the patterns in complex ways. You can also use
them to launch programmatic actions that depend on patterns.
A tongue-in-cheek comment by programmers is worth thinking about: "Sometimes you
have a programming problem and it seems like the best solution is to use regular
expressions now you have two problems." Regular expressions are amazingly
powerful and deeply expressive. That is the very reason writing them is just as
error-prone as writing any other complex programming code. It is always better to
solve a genuinely simple problem in a simple way when you go beyond simple, think
about regular expressions.
Tutorial: Using regular expressions
標(biāo)簽：
expression
the
tutorial
regular
上傳時(shí)間：
2013-12-19
上傳用戶：sardinescn
-
On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標(biāo)簽：
demonstrates
sequential
Selection
Bayesian
上傳時(shí)間：
2016-04-07
上傳用戶：lindor
-
MX21 CSI driver user mode library
*
* This program is free software you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation either version 2 of the License, or
* (at your option) any later version.
標(biāo)簽：
redistribute
software
library
program
上傳時(shí)間：
2016-04-10
上傳用戶：himbly
-
* This file is part of DigitalWatch, a free DTV watching and recording
* program for the VisionPlus DVB-T.
*
* DigitalWatch is free software you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation either version 2 of the License, or
* (at your option) any later version.
標(biāo)簽：
DigitalWatch
VisionPlu
recording
watching
上傳時(shí)間：
2014-08-27
上傳用戶：水口鴻勝電器
-
* This file is part of DigitalWatch, a free DTV watching and recording
* program for the VisionPlus DVB-T.
*
* DigitalWatch is free software you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation either version 2 of the License, or
* (at your option) any later version.
標(biāo)簽：
DigitalWatch
VisionPlu
recording
watching
上傳時(shí)間：
2013-12-18
上傳用戶：dongbaobao
-
This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標(biāo)簽：
sequential
reversible
algorithm
nstrates
上傳時(shí)間：
2014-01-18
上傳用戶：康郎
-
This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
標(biāo)簽：
reversible
algorithm
the
nstrates
上傳時(shí)間：
2014-01-08
上傳用戶：cuibaigao
-
JLAB is a set of Matlab functions I have written or co-written over the past fifteen years for the purpose of analyzing data. It consists of four hundred m-files spanning thirty thousand lines of code. JLAB includes functions ranging in complexity from one-line aliases to high-level algorithms for certain specialized tasks. These have been collected together and made publicly available for you to use, modify, and --- subject to certain very reasonable constraints --- to redistribute.
Some of the highlights are: a suite of functions for the rapid manipulation of multi-component, potentially multi-dimensional datasets a systematic way of dealing with datasets having components of non-uniform length tools for fine-tuning figures using compact, straightforward statements and specialized functions for spectral and time / frequency analysis, including advanced wavelet algorithms developed by myself and collaborators.
標(biāo)簽：
co-written
functions
the
fifteen
上傳時(shí)間：
2014-01-26
上傳用戶：hjshhyy
-
** File name: target.h
** Last modified Date: 2004-09-17
** Last Version: 1.0
** Descriptions: header file of the specific codes for LPC2100 target boards
** Every project should include a copy of this file, user may modify it as ne
標(biāo)簽：
Last
Description
modified
Version
上傳時(shí)間：
2014-05-30
上傳用戶：wanghui2438
-
Of the password is:
Server: "1."
Client: + for the month of the date of the machine. Such as "2005/08/05", compared with the number "85"
Database: "xzxq".
I made the changes:
1, stations and customer-service once every 30 seconds to exchange information (to ensure continuous line)
2, computer services-an increase of the serial number
3, client-service to send the card serial number and send IP addresses to the service side
4, the desktop client by the embargo, since the definition of the icon to start the process faster (from the window Superman Code)
5, CS-shielding some function keys, but CTRL + ALT + DEL keys can not shield the hope that a revised modify these friends
6, there are some corners of Laws (such as title, etc.).
Client desktop icon in the Settings page set up first class to enter FXZWN999 open on to add, delete icon button
標(biāo)簽：
the
password
machine
Client
上傳時(shí)間：
2016-06-27
上傳用戶：xsnjzljj
