Added missing transpose

ULAFF · May 9, 2014 · 9a9aec1 · 9a9aec1
1 parent 7fff869
commit 9a9aec1
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diff --git a/12.4.2 The Power Method.ipynb b/12.4.2 The Power Method.ipynb
@@ -128,7 +128,7 @@
       " </ul>\n",
       " \n",
       "If you change the \"3\" on the diagonal to \"-4\", then you have two largest eigenvalues (in magnitude), and the vector $ x $ will end up in the space spanned by $ v_0 $ and $ v_1 $. \n",
-      " You can check this by looking at $ ( I - V_L ( V_L^T V_L )^{-1} V_L ) x $, where $V_L $ equals the matrix with $ v_0 $ and $ v_1 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_L ) $ converges to zero. This is seen in the following code block:\n",
+      " You can check this by looking at $ ( I - V_L ( V_L^T V_L )^{-1} V_L^T ) x $, where $V_L $ equals the matrix with $ v_0 $ and $ v_1 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_L ) $ converges to zero. This is seen in the following code block:\n",
       "\n"
      ]
     },

diff --git a/12.5.1 The Inverse Power Method.ipynb b/12.5.1 The Inverse Power Method.ipynb
@@ -156,7 +156,7 @@
       " \n",
       " Try changing the \"2\" to a \"-1\" or \"1\".  What happens then?\n",
       " \n",
-      " You can check this by looking at $ ( I - V_R ( V_R^T V_R )^{-1} V_R ) x $, where $V_R $ equals the matrix with $ v_2 $ and $ v_3 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_R ) $ converges to zero. This is seen in the following code block:\n"
+      " You can check this by looking at $ ( I - V_R ( V_R^T V_R )^{-1} V_R^T ) x $, where $V_R $ equals the matrix with $ v_2 $ and $ v_3 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_R ) $ converges to zero. This is seen in the following code block:\n"
      ]
     },
     {

diff --git a/12.5.2 Shifting the Inverse Power Method.ipynb b/12.5.2 Shifting the Inverse Power Method.ipynb
@@ -165,7 +165,7 @@
       " \n",
       " This time, if you change the \"2\" on the diagonal to \"-1\", you still converge to $ v_{n-1} $ because for the matrix $ A - \\mu I $, $ -1 - \\mu $ is not as small as $ 1 - \\mu $ (in magnitude).\n",
       "\n",
-      " You can check this by looking at $ ( I - V_R ( V_R^T V_R )^{-1} V_R ) x $, where $V_R $ equals the matrix with $ v_2 $ and $ v_3 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_R ) $ converges to zero. This is seen in the following code block:\n"
+      " You can check this by looking at $ ( I - V_R ( V_R^T V_R )^{-1} V_R^T ) x $, where $V_R $ equals the matrix with $ v_2 $ and $ v_3 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_R ) $ converges to zero. This is seen in the following code block:\n"
      ]
     },
     {
-Original file line number
+Diff line change
@@ Expand Up / @@ -156,7 +156,7 @@ @@
           " \n",
           " Try changing the \"2\" to a \"-1\" or \"1\".  What happens then?\n",
           " \n",
-          " You can check this by looking at $ ( I - V_R ( V_R^T V_R )^{-1} V_R ) x $, where $V_R $ equals the matrix with $ v_2 $ and $ v_3 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_R ) $ converges to zero. This is seen in the following code block:\n"
+          " You can check this by looking at $ ( I - V_R ( V_R^T V_R )^{-1} V_R^T ) x $, where $V_R $ equals the matrix with $ v_2 $ and $ v_3 $ as its columns, to see if the vector orthogonal to $ {\\cal C}( V_R ) $ converges to zero. This is seen in the following code block:\n"
          ]
         },
         {
@@ Expand Down @@