Least-sqaures approximation Flashcards

1
Q

What is the main question in this chapter?

A

How do we find approximate solutions to overdetermined systems?

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2
Q

What is an overdetermined system?

A

If A is an m x n rectangular matrix with m > n, then the linear system a Ax = b is overdetermined and will usually have no solutions.

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3
Q

Define the inner product.

A
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4
Q

What norm is the inner product related to? And why?

A
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5
Q

What is the angle θ between x and y given by?

A
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6
Q

Define orthogonal.

A
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7
Q

When is the set S = {x1, x2, …. , xn} orthogonal?

A
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8
Q

What is the theorem about an orthogonal set being a basis?

A
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9
Q

Prove the following theorem.

A
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10
Q

Define an orthonormal set.

A
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11
Q

Given an orthogonal set S, how can you construct an orthonomal set S’?

A
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12
Q

What is the theorem about the columns of a matrix Q being an orthonormal set?

A
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13
Q

Prove the following theorem.

A
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14
Q

Inner products are preserved under multiplication of what?

A

Orthogonal matrices

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15
Q

Show that inner products are preserved under multiplication by orthogonal matrices.

A
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16
Q

What is the discrete least squares problem?

A

Find x that minimizes the l2 norm of the residual ||Ax - b||2

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17
Q

What is the range(A)?

A

The set of all possible bectors Ax ∈ ℝm, where x ∈ ℝn.

18
Q

Why is the range(A) only a subspace of ℝm?

A

Because Ax is a linear combination of columns of A and there are only n < m of them, and in particular it will not, in general, contain b.

19
Q

In discrete least squares what are we looking to minimise?

A
20
Q

How do you minimise ||r||2?

A

By choosing r orthogonal to Ax

21
Q

When minimising ||r||2 what equation is satisfied?

A
22
Q

What is the following equation called?

A

The normal equation

23
Q

Prove the following equation is satisfied when minimsing ||r||2.

A
24
Q

What is the theorem about if a matrix ATA is invertible?

A
25
Q

Prove the following theorem.

A
26
Q

What is the QR decomposition theorem?

A
27
Q

What is the fastest way to compute Q and R?

A

Gram-Schmidt orthogonalization.

28
Q

What is the algorithm for Gram-Schmidt

A
29
Q

How can you construct QR decomposition of A?

A

Apply Gram-Schmidt to the set of columns of A, this produces a set of orthogonal vectors qi. Then you write A in the following form.

30
Q

How does QR decomposition help in least squares?

A
31
Q

What is the continuous least squares problem?

A

It is to find a polynomial pn ∈ PN that minimises ||pn - f||, in a given inner product.

32
Q

Define an inner product.

A
33
Q

What does w(x) stand for in the following?

A

The weight function

34
Q

What is the purpose of the weight function?

A

To assign varying degrees of importance to errors on different portions of the interval

35
Q

Define the norm ||f|| using the following inner product.

A
36
Q

What is the continuous least squares theorem?

A
37
Q

Prove the following theorem.

A
38
Q

Define a family of orthogonal polynomials.

A
39
Q

What are the three options for normalising a family or orthogonal polynomials?

A
40
Q

What is the three-term recurrence theorem?

A
41
Q

Prove the following theorem.

A
42
Q
A