Subsection 6.1.2 Overview
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6.1 Opening Remarks
6.1.1 Whose problem is it anyway?
6.1.2 Overview
6.1.3 What you will learn
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6.2 Floating Point Arithmetic
6.2.1 Storing real numbers as floating point numbers
6.2.2 Error in storing a real number as a floating point number
6.2.3 Models of floating point computation
6.2.4 Stability of a numerical algorithm
6.2.5 Conditioning versus stability
6.2.6 Absolute value of vectors and matrices
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6.3 Error Analysis for Basic Linear Algebra Algorithms
6.3.1 Initial insights
6.3.2 Backward error analysis of dot product: general case
6.3.3 Dot product: error results
6.3.4 Matrix-vector multiplication
6.3.5 Matrix-matrix multiplication
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6.4 Error Analysis for Solving Linear Systems
6.4.1 Numerical stability of triangular solve
6.4.2 Numerical stability of LU factorization
6.4.3 Numerical stability of linear solve via LU factorization
6.4.4 Numerical stability of linear solve via LU factorization with partial pivoting
6.4.5 Is LU with Partial Pivoting Stable?
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6.5 Enrichments
6.5.1 Systematic derivation of backward error analyses
6.5.2 LU factorization with pivoting can fail in practice
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6.6 Wrap Up
6.6.1 Additional homework
6.6.2 Summary