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node10.html
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<!DOCTYPE html>
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<html>
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<title>图片清单</title>
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<meta name="description" content="图片清单">
<meta name="keywords" content="book, math, eigenvalue, eigenvector, linear algebra, sparse matrix">
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<h2><a name="SECTION00800000000000000000">图片清单</a></h2>
<ol>
<li><a name="tex2html4" href="node19.html#1049">阻尼振动质量-弹簧系统。</a>
<li><a name="tex2html19" href="node114.html#7915">残差估计，L形薄膜矩阵。</a>
<li><a name="tex2html20" href="node114.html#7921">Ritz值，L形薄膜矩阵。</a>
<li><a name="tex2html21" href="node114.html#7935">残差估计，Medline SVD矩阵</a>
<li><a name="tex2html22" href="node114.html#7940">残差估计，位移-反演L形薄膜矩阵。</a>
<li><a name="tex2html25" href="node147.html#10618">针对外部特征值的Jacobi-Davidson方法，采用多种策略求解校正方程。</a>
<li><a name="tex2html26" href="node147.html#10627">针对外部特征值（顶部）和内部特征值（底部）的Jacobi-Davidson方法。校正方程通过5步普通GMRES（左侧）和5步预处理GMRES（右侧）求解。</a>
<li><a name="tex2html29" href="node174.html#17624">残差估计，采用位移-反演的Lanczos方法，L形薄膜9点有限差分近似。</a>
<li><a name="tex2html36" href="node208.html#27088">通过直接平衡和不直接平衡计算的QH<span class="math-inline">768</span>和TOLOSA矩阵特征值的相对精度。</a>
<li><a name="tex2html37" href="node208.html#27089">通过Krylov平衡和不平衡计算的QH<span class="math-inline">768</span>和TOLOSA矩阵特征值的相对精度。</a>
<li><a name="tex2html38" href="node208.html#27090">不同Krylov平衡算法下，QH<span class="math-inline">768</span>矩阵最大和最小（按模）特征值相对精度的比较，使用默认设置的五次迭代和<span class="math-inline">10^{-8}</span>截止值。</a>
<li><a name="tex2html39" href="node208.html#27091">不同Krylov平衡算法下，TOLOSA矩阵最大和最小（按模）特征值相对精度的比较，使用默认设置的五次迭代和<span class="math-inline">10^{-8}</span>截止值。</a>
<li><a name="tex2html45" href="node274.html#26946">针对外部特征值（左侧）和内部特征值（右侧）的Jacobi-Davidson方法。</a>
<li><a name="tex2html48" href="node294.html#36421">BFW<span class="math-inline">782</span>的收敛历史。</a>
<li><a name="tex2html56" href="node354.html#43545">Procrustes问题</a>
<li><a name="tex2html57" href="node355.html#43560">Jordan问题</a>
<li><a name="tex2html58" href="node356.html#43576">迹最小化问题</a>
<li><a name="tex2html59" href="node357.html#43589">LDA玩具问题</a>
<li><a name="tex2html60" href="node358.html#43604">同时Schur问题</a>
<li><a name="tex2html61" href="node359.html#43616">同时对角化问题</a>
<li><a name="tex2html62" href="node367.html#43821">无约束微分<span class="math-inline">F(Y)</span>可以投影到切空间以获得协变梯度<span class="math-inline">G</span>。</a>
<li><a name="tex2html63" href="node369.html#43850">在平坦空间中，比较邻近点的向量没有问题，因为所有向量都位于同一切空间中。</a>
<li><a name="tex2html64" href="node369.html#43857">在弯曲流形中，比较邻近点的向量可能导致向量不在切空间中。</a>
<li><a name="tex2html65" href="node378.html#46558">非对称天际线或变带宽矩阵的轮廓。</a>
<li><a name="tex2html69" href="node408.html#48517">Olmstead问题的非精确有理Krylov方法残差范数的对数图。圆圈表示<span class="math-inline">\Vert f_j\Vert</span>，实心点表示<span class="math-inline">\Vert r_j\Vert</span>。</a>
<li><a name="tex2html70" href="node419.html#49095">共轭梯度与最速上升比较，<span class="math-inline">\delta _1 / \delta _0=10</span></a>
<li><a name="tex2html71" href="node419.html#49102">共轭梯度与最速上升比较，<span class="math-inline">\delta _1 / \delta _0=100</span></a>
<li><a name="tex2html72" href="node419.html#49109">共轭梯度与最速上升比较，<span class="math-inline">\delta _1 / \delta _0=1000</span></a>
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<button class="navigate">索引</button></a>
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<b>下一节：</b><a name="tex2html808" href="node11.html">表格清单</a>
<b>上一级：</b><a name="tex2html802" href="index.html">首页</a>
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<address>
Susan Blackford
2000-11-20
</address>
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