recap: norms

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Recap: Norms What’s a norm? Dene norm.

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Page 1: Recap: Norms

Recap: NormsWhat’s a norm?

Define norm.

Page 2: Recap: Norms

Norms: Examples

Examples of norms?

Demo: Vector Norms [cleared]

Page 3: Recap: Norms

Norms: Which one?

Does the choice of norm really matter much?

Page 4: Recap: Norms

Norms and Errors

If we’re computing a vector result, the error is a vector.That’s not a very useful answer to ‘how big is the error’.What can we do?

Page 5: Recap: Norms

Forward/Backward ErrorSuppose want to compute y = f (x), but approximate y = f (x).

What are the forward error and the backward error?

Page 6: Recap: Norms

Forward/Backward Error: Example

Suppose you wanted y =√2 and got y = 1.4.

What’s the (magnitude of) the forward error?

Page 7: Recap: Norms

Forward/Backward Error: Example

Suppose you wanted y =√2 and got y = 1.4.

What’s the (magnitude of) the backward error?

Page 8: Recap: Norms

Forward/Backward Error: Observations

What do you observe about the relative manitude of the relative errors?

Page 9: Recap: Norms

Sensitivity and Conditioning

What can we say about amplification of error?

Page 10: Recap: Norms

Example: Condition Number of Evaluating a Function

y = f (x). Assume f differentiable.

Demo: Conditioning of Evaluating tan [cleared]

Page 11: Recap: Norms

Stability and AccuracyPreviously: Considered problems or questions.Next: Considered methods, i.e. computational approaches to find solutions.When is a method accurate?

When is a method stable?