<?xml version="1.0" encoding="utf-8"?><?xml-stylesheet href='http://feeds.feedsky.com/styles/temp01.xsl' type='text/xsl' ?><!--这是一个由Feedsy提供技术支持的Feed，为了提高读者阅读的体验，以及满足用户美化自己Feed的需要，我们设计了多种精美的Feed模板，提供给大家选择，所有最终呈现出来的样式，皆由用户自愿选择使用，未经许可，任何团体和个人，请不要擅自修改样式或者盗用，这是对于用户选择权的尊重。--><rss xmlns:atom="http://www.w3.org/2005/Atom" xmlns:fs="http://www.feedsky.com/namespace/feed" xmlns:wfw="http://wellformedweb.org/CommentAPI/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" xmlns:trackback="http://madskills.com/public/xml/rss/module/trackback/" xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0"><channel><atom:link href="http://feeds.feedsky.com/csdn.net/BoyMgl" type="application/rss+xml" ref="self"></atom:link><fs:self_link href="http://feeds.feedsky.com/csdn.net/BoyMgl" type="application/rss+xml"></fs:self_link><lastBuildDate>Sun, 06 Jul 2008 22:54:00 GMT</lastBuildDate><title>MiGL Tech.</title><description>苟利国家生死以，岂因祸福避趋之~</description><item><title>C/C++ 中的移位操作拾遗</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/90530174/1183125/1/item.html</link><wfw:comment>comments/2619264.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/2619264.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=2619264</trackback:ping><description>C\C++中移位操作应注意的几点问题&lt;img src =&quot;aggbug/2619264.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Mon, 07 Jul 2008 06:54:00 +0800</pubDate><author>米国梁</author><comments>http://blog.csdn.net/BoyMgl/archive/2008/07/06/2619264.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2008/07/06/2619264.aspx</guid><dc:creator>米国梁</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2008/07/06/2619264.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/90530174/1183125</fs:itemid></item><item><title>别把自己的年轻丢了</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824151/1183125/1/item.html</link><wfw:comment>comments/2579950.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/2579950.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=2579950</trackback:ping><description>&lt;p&gt;你还年轻吗？&lt;/p&gt;&lt;p&gt;1、你还敢与接受挑战吗？别着急回答敢，我想说的是，如果你是个热衷于软件，那么让你去搬钢板一个月，你仍能笑容依旧吗？&lt;/p&gt;&lt;p&gt;2、你还敢问为什么吗？不懂装懂的事情屡见不鲜，位的就是一张破脸，到头来你也不知道你会不会，更不知道你对面的那个人会不会。&lt;/p&gt;&lt;p&gt;3、你还敢把你的理想和大家分享吗？年少轻狂，所以不畏闯荡，所以能够面对任何冷嘲热讽，怕什么也不怕犯错，因为我有时间改正，更有信心可以超越。&lt;/p&gt;&lt;p&gt;4、你还能为你热衷的执着吗？你能为一个东西执着10年吗？在这十年里，哪怕将来也是，如果你去的成就的概率和买彩票一样，你还能无悔过去的坚持吗？还能无悔的继续坚持吗？&lt;/p&gt;&lt;p&gt;5、你还敢想吗？就是胡思乱想，什么都敢想，并不区分异想天开何白日做梦，乐此不疲！&lt;/p&gt;&lt;p&gt;6、你还敢说你年轻吗？&lt;/p&gt;&lt;img src =&quot;aggbug/2579950.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Tue, 24 Jun 2008 03:13:00 +0800</pubDate><author>米国梁</author><comments>http://blog.csdn.net/BoyMgl/archive/2008/06/23/2579950.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2008/06/23/2579950.aspx</guid><dc:creator>米国梁</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2008/06/23/2579950.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824151/1183125</fs:itemid></item><item><title>被唐勇点了，回答了~</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824152/1183125/1/item.html</link><wfw:comment>comments/2208522.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/2208522.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=2208522</trackback:ping><description>被人点名了，这些问题我比较喜欢~&lt;img src =&quot;aggbug/2208522.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Sun, 23 Mar 2008 18:20:00 +0800</pubDate><author>米国梁</author><comments>http://blog.csdn.net/BoyMgl/archive/2008/03/23/2208522.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2008/03/23/2208522.aspx</guid><dc:creator>米国梁</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2008/03/23/2208522.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824152/1183125</fs:itemid></item><item><title>有理函数内插法和外推法算法实现</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824153/1183125/1/item.html</link><wfw:comment>comments/1933370.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1933370.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1933370</trackback:ping><description>有理函数比多项式函数优越，是因为有理函数能够模拟具有极点的函数。极点是指（1）式中分母的零点。如果要插值的函数本身有极点的话，则在实数x处就有可能出现这些极点。&lt;img src =&quot;aggbug/1933370.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Fri, 14 Dec 2007 00:29:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/13/1933370.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/13/1933370.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/13/1933370.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824153/1183125</fs:itemid></item><item><title>多项式内插法和外推法算法实现</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824154/1183125/1/item.html</link><wfw:comment>comments/1931286.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1931286.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1931286</trackback:ping><description>首先讨论了lagrangian(拉格朗日)插值多项式，分析出不适合编程，而后讨论了更好的方法——neville插值多项式进行插值运算。&lt;img src =&quot;aggbug/1931286.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Wed, 12 Dec 2007 21:14:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/12/1931286.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/12/1931286.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/12/1931286.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824154/1183125</fs:itemid></item><item><title>线性方程组解的迭代改进算法实现</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824155/1183125/1/item.html</link><wfw:comment>comments/1929054.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1929054.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1929054</trackback:ping><description>在直接求解线性方程组的方法中，舍入误差累积到一定程度时矩阵就接近歧义了。对于远非奇异的矩阵，也容易丢失两个或三个有效数字。如果这种情况发生，有一个简单的方法能够恢复到整个及其精度，称为解的迭代改进，这在理论上是很直接的。&lt;img src =&quot;aggbug/1929054.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Tue, 11 Dec 2007 19:48:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/11/1929054.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/11/1929054.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/11/1929054.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824155/1183125</fs:itemid></item><item><title>带状对角矩阵的LU分解及回代求解算法实现</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824156/1183125/1/item.html</link><wfw:comment>comments/1926091.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1926091.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1926091</trackback:ping><description>分解主要是使用笔者前面几篇文章提到过的Crout方法。因为不可能把一个带状对角矩阵A的LU分解也像其压缩形式本是一样紧凑的存储起来，因为分解产生了附加的非零元素填入。一种直接的存储方案是，坝上三角因子（U）返回到以前占有的相同的空间中，把下三角因子（L）返回到单独的N×m1压缩矩阵中。U的对角线元素被存放在A的存储空间的第一列。&lt;img src =&quot;aggbug/1926091.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Mon, 10 Dec 2007 07:04:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/09/1926091.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/09/1926091.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/09/1926091.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824156/1183125</fs:itemid></item><item><title>带状对角矩阵的压缩及乘法运算算法实现</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824157/1183125/1/item.html</link><wfw:comment>comments/1920687.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1920687.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1920687</trackback:ping><description>带状对角系统紧靠在对角线左边（下边）有m1≥0个非零元素，紧靠其右边（上边）有m2≥0个非零元素。当然，这仅在m1和m2&lt;&lt;N时才有意义。这种情况下，用LU分解求解线性系统可以比通用N×N的情况完成的更快，占用空间更少。&lt;img src =&quot;aggbug/1920687.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Thu, 06 Dec 2007 21:36:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/06/1920687.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/06/1920687.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/06/1920687.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824157/1183125</fs:itemid></item><item><title>求解三对角系统方程算法实现</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824158/1183125/1/item.html</link><wfw:comment>comments/1915987.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1915987.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1915987</trackback:ping><description>线性方程系统的特例之一是三对角形式的，也就是说，非零的元素仅出现在对角线及其前、后一列的位置上。&lt;img src =&quot;aggbug/1915987.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Tue, 04 Dec 2007 22:36:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/04/1915987.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/04/1915987.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/04/1915987.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824158/1183125</fs:itemid></item><item><title>求矩阵行列式的值（基于LU分解法）</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824159/1183125/1/item.html</link><wfw:comment>comments/1914560.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1914560.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1914560</trackback:ping><description>对矩阵进行LU分解，显然，分解后的矩阵对角线上元素的乘积即为原始矩阵行列式的值&lt;img src =&quot;aggbug/1914560.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Tue, 04 Dec 2007 06:53:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/03/1914560.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/03/1914560.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/03/1914560.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824159/1183125</fs:itemid></item><item><title>矩阵求逆算法实现（基于LU分解法）</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824160/1183125/1/item.html</link><wfw:comment>comments/1914288.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1914288.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1914288</trackback:ping><description>LU分解大约需要执行N3/3次内层循环（每次包括一次乘法和一次加法）。这是求解一个（或少量几个）右端项时的运算次数，它要比Gauss-Jordan消去法快三倍，比不计算逆矩阵的Gauss-Jordan法快1.5倍。&lt;img src =&quot;aggbug/1914288.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Tue, 04 Dec 2007 03:14:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/03/1914288.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/03/1914288.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/03/1914288.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824160/1183125</fs:itemid></item><item><title>LU分解法求解线性方程组</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824161/1183125/1/item.html</link><wfw:comment>comments/1913199.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1913199.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1913199</trackback:ping><description>LU分解法的原理以及实现，并求解线性方程组。&lt;img src =&quot;aggbug/1913199.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Mon, 03 Dec 2007 18:15:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/03/1913199.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/03/1913199.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/03/1913199.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824161/1183125</fs:itemid></item><item><title>Gauss-Jordan消去法中完全选主元法求解线性方程组</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824162/1183125/1/item.html</link><wfw:comment>comments/1910213.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1910213.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1910213</trackback:ping><description>完全选主元法在数学上与部分选主元法的效果是相同的。完全选主元法区别于部分选主元法在于行和列都要进行交换。&lt;img src =&quot;aggbug/1910213.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Sat, 01 Dec 2007 17:50:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/12/01/1910213.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/12/01/1910213.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/12/01/1910213.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824162/1183125</fs:itemid></item><item><title>双三次B样条曲面生成算法实现（非OpenGL）</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824163/1183125/1/item.html</link><wfw:comment>comments/1907273.aspx</wfw:comment><slash:comments>0</slash:comments><wfw:commentRss>comments/commentRss/1907273.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1907273</trackback:ping><description>今天刚写了个双三次B样条曲面的生成算法的实现，同样没有使用OpenGL&lt;img src =&quot;aggbug/1907273.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Thu, 29 Nov 2007 23:40:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/11/29/1907273.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/11/29/1907273.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/11/29/1907273.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824163/1183125</fs:itemid></item><item><title>贝塞尔曲面的绘制</title><link>http://item.feedsky.com/~csdn.net/BoyMgl/~1183144/86824164/1183125/1/item.html</link><wfw:comment>comments/1904140.aspx</wfw:comment><slash:comments>1</slash:comments><wfw:commentRss>comments/commentRss/1904140.aspx</wfw:commentRss><trackback:ping>http://tb.blog.csdn.net/TrackBack.aspx?PostId=1904140</trackback:ping><description>网上很少有贝塞尔曲面运算的例子，大多都是OpenGL的，我自己写了一个，共需要的朋友参考一下o(∩_∩)o...&lt;img src =&quot;aggbug/1904140.aspx&quot; width = &quot;1&quot; height = &quot;1&quot; /&gt;</description><pubDate>Tue, 27 Nov 2007 22:19:00 +0800</pubDate><author>BoyMgl</author><comments>http://blog.csdn.net/BoyMgl/archive/2007/11/27/1904140.aspx#Feedback</comments><guid isPermaLink="false">http://blog.csdn.net/BoyMgl/archive/2007/11/27/1904140.aspx</guid><dc:creator>BoyMgl</dc:creator><fs:srclink>http://blog.csdn.net/BoyMgl/archive/2007/11/27/1904140.aspx</fs:srclink><fs:srcfeed>http://blog.csdn.net/BoyMgl/rss.aspx</fs:srcfeed><fs:itemid>csdn.net/BoyMgl/~1183144/86824164/1183125</fs:itemid></item></channel></rss>