代码搜索:computing
找到约 6,514 项符合「computing」的源代码
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www.eeworm.com/read/158865/5594342
c input.c
/* Input handling for G++.
Copyright (C) 1992, 93-98, 1999 Free Software Foundation, Inc.
Written by Ken Raeburn (raeburn@cygnus.com) while at Watchmaker Computing.
This file is part of GNU CC.
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cpp haney.cpp
// Haney's induction calculation benchmark.
//
// See: Scott W. Haney, Is C++ Fast Enough for Scientific Computing?
// Computers in Physics Vol. 8 No. 6 (1994), p. 690
//
// Arch D. Ro
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txt covfft.inp.txt
COVFFT EXAMPLE
UNIX batch job for computing covariance functions and power spectra
from gravity anomalies by FFT:
covfft
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c ns820.c
/* ns820.c: A Linux Gigabit Ethernet driver for the NatSemi DP83820 series. */
/*
Written/copyright 1999-2003 by Donald Becker.
Copyright 2002-2003 by Scyld Computing Corporation.
This software ma
www.eeworm.com/read/413630/11149191
java realdoublefft_even.java
package jnt.FFT;
/** Computes FFT's of real, double precision data when n is even, by
* computing complex FFT.
*
* @author Bruce R. Miller bruce.miller@nist.gov
* @author Derived from Numerica
www.eeworm.com/read/135011/13967168
log buildchk.log
BUILD: Computing Include file dependencies:
BUILD: Examining e:\d12isodriver directory for files to compile.
Compiling e:\d12isodriver directory ********************
'nmake.exe /c BUILDMSG=Stop. -i NT
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cpp haney.cpp
// Haney's induction calculation benchmark.
//
// See: Scott W. Haney, Is C++ Fast Enough for Scientific Computing?
// Computers in Physics Vol. 8 No. 6 (1994), p. 690
//
// Arch D. Robison,
www.eeworm.com/read/113590/15452548
h pci-scan.h
#ifndef _PCI_SCAN_H
#define _PCI_SCAN_H
/*
version 1.02 $Version:$ $Date: 2001/03/18 21:35:59 $
Copyright 1999-2001 Donald Becker / Scyld Computing Corporation
This software is part of th
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h t128.h
/*
* Trantor T128/T128F/T228 defines
* Note : architecturally, the T100 and T128 are different and won't work
*
* Copyright 1993, Drew Eckhardt
* Visionary Computing
* (Unix and Linux cons
www.eeworm.com/read/386050/8767386
m som.m
function W = som(a,k,nrruns,eta,h)
%SOM Simple routine computing a Self-Organizing Map (SOM)
%
% W = SOM(X,K)
%
% Train a 2D SOM on dataset X. In K the size of the map is defined. The