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Orthogonal projections

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Intro to orthogonal projection onto a subspace

Intro to orthogonal projection onto a subspace

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Intro to orthogonal projection onto a subspace

14:35

About this lesson

Orthogonal Projections Overview:
The Orthogonal Decomposition Theorem
• Make \(y\) as the sum of two vectors \(\hat{y}\) and \(z\)
• Orthogonal basis \(\)→\(\) \(\hat{y}= \frac{y \cdot v_1}{v_1 \cdot v_1}v_1 + \cdots + \frac{y \cdot v_p}{v_p \cdot v_p}v_p\)
• Orthonormal basis \(\)→\(\) \(\hat{y}=(y\cdot v_1)v_1+\cdots +(y\cdots v_p)v_p\)
• \(z=y - \hat{y}\)

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Video 1 of 8

Intro to orthogonal projection onto a subspace

15 min

Selected

Property: projection of y onto S equals y when y is in S

4 min

Best approximation theorem and finding the closest point in a subspace

12 min

Decomposing y into orthogonal components using projection onto span of V1

11 min

Verifying orthonormality and computing an orthogonal projection

12 min

Best approximation of y using orthogonal projection onto span of two vectors

10 min

Finding the closest point to y using orthogonal projection

9 min

Finding the closest distance from a vector to a subspace

11 min