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5: Linear Algebra and Computing

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    82498
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    • 5.1: Gaussian Elimination Revisited
      In this section, we revisit Gaussian elimination and explore some problems with implementing it in the straightforward way that we described back in Section 1.2. In particular, we will see how the fact that computers only approximate arithmetic operations can lead us to find solutions that are far from the actual solutions. Second, we will explore how much work is required to implement Gaussian elimination and devise a more efficient means of implementing it.
    • 5.2: Finding Eigenvectors Numerically
      In this section, we will explore a technique called the power method that finds numerical approximations to the eigenvalues and eigenvectors of a square matrix. Generally speaking, this method is how eigenvectors are found in practical computing applications.


    This page titled 5: Linear Algebra and Computing is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by David Austin via source content that was edited to the style and standards of the LibreTexts platform.