From 36baa00a6086f153ba7e3fb5a89e5db94a7e598b Mon Sep 17 00:00:00 2001 From: austinwn Date: Wed, 14 May 2014 17:43:46 -0500 Subject: [PATCH] Week 12 Mark edits --- 12.5.1 The Inverse Power Method.ipynb | 2 +- 12.5.2 Shifting the Inverse Power Method.ipynb | 2 +- 12.5.3 The Rayleigh Quotient Iteration.ipynb | 4 ++-- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/12.5.1 The Inverse Power Method.ipynb b/12.5.1 The Inverse Power Method.ipynb index 04d0468..fc35f2c 100644 --- a/12.5.1 The Inverse Power Method.ipynb +++ b/12.5.1 The Inverse Power Method.ipynb @@ -122,7 +122,7 @@ " x = x / np.sqrt( np.transpose( x ) * x )\n", " \n", " # Notice we compute the Rayleigh quotient with matrix A, not Ainv. This is because\n", - " # the eigenvalue of A is an eigenvalue of Ainv\n", + " # the eigenvector of A is an eigenvector of Ainv\n", " \n", " print( 'Rayleigh quotient with vector x:', np.transpose( x ) * A * x / ( np.transpose( x ) * x ))\n", " print( 'inner product of x with v3 :', np.transpose( x ) * V[ :, 3 ] )\n", diff --git a/12.5.2 Shifting the Inverse Power Method.ipynb b/12.5.2 Shifting the Inverse Power Method.ipynb index 9044898..0dbc09a 100644 --- a/12.5.2 Shifting the Inverse Power Method.ipynb +++ b/12.5.2 Shifting the Inverse Power Method.ipynb @@ -131,7 +131,7 @@ " x = x / np.sqrt( np.transpose( x ) * x )\n", " \n", " # Notice we compute the Rayleigh quotient with matrix A, not Ainv. This is because\n", - " # the eigenvalue of A is an eigenvalue of Ainv\n", + " # the eigenvector of A is an eigenvector of Ainv\n", " \n", " print( 'Rayleigh quotient with vector x:', np.transpose( x ) * A * x / ( np.transpose( x ) * x ))\n", " print( 'inner product of x with v3 :', np.transpose( x ) * V[ :, 3 ] )\n", diff --git a/12.5.3 The Rayleigh Quotient Iteration.ipynb b/12.5.3 The Rayleigh Quotient Iteration.ipynb index f7de5b9..0d3365c 100644 --- a/12.5.3 The Rayleigh Quotient Iteration.ipynb +++ b/12.5.3 The Rayleigh Quotient Iteration.ipynb @@ -132,9 +132,9 @@ " x = x / np.sqrt( np.transpose( x ) * x )\n", " \n", " # Notice we compute the Rayleigh quotient with matrix A, not Ainv. This is because\n", - " # the eigenvalue of A is an eigenvalue of Ainv\n", + " # the eigenvector of A is an eigenvector of Ainv\n", " \n", - " mu = np.transpose( x ) * A * x / ( np.transpose( x ) * x )\n", + " mu = np.transpose( x ) * A * x\n", " \n", " # The above returns a 1 x 1 matrix. Let's set mu to the scalar\n", " \n",