Tug of War(A tug of war is to be arranged at the local office picnic. For the tug of war, the picnickers must be divided into two teams. Each person must be on one team or the other the Number of people on the two teams must not differ by more than 1 the total weight of the people on each team should be as nearly equal as possible. The first line of input contains n the Number of people at the picnic. n lines follow. The first line gives the weight of person 1 the second the weight of person 2 and so on. Each weight is an integer between 1 and 450. There are at most 100 people at the picnic. Your output will be a single line containing 2 Numbers: the total weight of the people on one team, and the total weight of the people on the other team. If these Numbers differ, give the lesser first. )
上传时间： 2014-01-07
上传用户：离殇
The Gray Watson debugging malloc library is C source code for a drop in replacement for the system malloc & other memory manage ment routines. What is unique about this library is that it contains a Number of powerful debugging facilities including very comprehensive heap testing and ex- cellent run-time debugging information.
标签： replacement debugging for library
上传时间： 2015-02-05
上传用户：TF2015
This program is to handle all possible arithmetic operations (+, -, *, /, %) and logic operations (, >=,
标签： operations arithmetic possible program
上传时间： 2015-03-23
上传用户：l254587896
This is a program that will let you calculate roots with the Quadratic formula (including complex roots), Factorial of a Number, Fibonacci series (and Pascals Triangle still under construction).
标签： Quadratic calculate including formula
上传时间： 2014-01-25
上传用户：zhuoying119
1. 实现原理： * 任何一个数都可以表示成指数形式，如下所示： * * N=nEe (0=<n的绝对值<=1,e为10的指数幂) * * 例如100可以表示成1E2,1001可以表示成1.01E3 * * 类 CBigNumber的成员Number为上述的n，exponent为上述的e * * 2. 如何使用这个类: * * 你可以把CBigNumber的头文件和实现函数加入你的工程，然后定义 * * 该类的实例，就可以对这些实例进行加减乘除了(详见示例程序)
标签：
上传时间： 2013-12-31
上传用户：gtf1207
This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the Number of time samples and M the Number of sources.
标签： instantaneous algorithm Bayesian Gaussian
上传时间： 2013-12-19
上传用户：jjj0202
This code implements the basic functions for an I2C slave device using the SSP module. All I2C functions are handled in an ISR. Bytes written to the slave are stored in a buffer. After a Number of bytes have been written, the master device can then read the bytes back from the buffer.
标签： implements I2C functions the
上传时间： 2015-04-02
上传用户：邶刖
This module can be used to interface to the MMC card in MMC or * SPI modes. It supports a multiple card environment. The reset and * identification processes assume multiple cards on the bus. * In MMC mode, the card Number is used as the RCA operand in the * commands.
标签： MMC interface multiple supports
上传时间： 2014-01-07
上传用户：qilin
VC技术内幕第五版_English.The 6.0 release of Visual C++ shows Microsoft s continued focus on Internet technologies and COM, which are key components of the new Windows Distributed interNet Application Architecture (DNA). In addition to supporting these platform initiatives, Visual C++ 6.0 also adds an amazing Number of productivity-boosting features such as Edit And Continue, IntelliSense, AutoComplete, and code tips. These features take Visual C++ to a new level. We have tried to make sure that this book keeps you up to speed on the latest technologies being introduced into Visual C++.
标签： Microsoft continued Internet English
上传时间： 2013-12-08
上传用户：lepoke
ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the Number of classes and produces keywords for each class. The icaML algorithm is used.
标签： ICA extension framework classify
上传时间： 2013-12-22
上传用户：himbly
