studEE16A
  • Introduction
  • Linear Algebra
    • Linear Equations
      • Description
      • Example Problems
    • Vector Spaces
      • Description
      • Example Problems
    • Inner Products
      • Description
      • Example Problems
    • Determinants
      • Description
      • Example Problems
    • Eigen-everything
      • Description
      • Example Problems
    • Matrices
      • Description
      • Example Problems
    • Least Squares
      • Description
      • Example Problems
    • Gram-Schmidt
      • Description
      • Example Problems
    • Basis
      • Description
      • Example Problems
    • Page Rank
  • Circuits
    • Circuit Basics
    • Capacitance
    • Nodal Analysis
    • Superposition
    • Thevenin and Norton
    • What, When, Where, and Why?
    • Op Amps
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  1. Linear Algebra

Gram-Schmidt

What and why

Gram-Schmidt is an important and useful algorithm to find an orthogonal basis for a set of vectors that spans that same subspace. Orthogonal (and orthonormal) bases have many advantages because they are easier to deal with. For example, solving a systems of equations using orthogonal bases just becomes projecting the vector onto each basis vector.

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Last updated 5 years ago

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