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* Understand the fundamentals of sampling theory: Nyquist frequency, aliasing | * Understand the fundamentals of sampling theory: Nyquist frequency, aliasing | ||
* Learn why and how to use anti-aliasing filters | * Learn why and how to use anti-aliasing filters | ||
- | * Reconstruct a signal from sampled data | + | |
- | * Examine the file structure of Neuralynx continuously sampled data in detail | + | Resources (optional): |
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- | Resources: | + | |
* (intuitive background) [[http://redwood.berkeley.edu/bruno/npb261/aliasing.pdf | nice, quick intro]] to aliasing by Bruno Olshausen, with some connections to the human visual system | * (intuitive background) [[http://redwood.berkeley.edu/bruno/npb261/aliasing.pdf | nice, quick intro]] to aliasing by Bruno Olshausen, with some connections to the human visual system | ||
- | * (more technical background, optional) read Chapter 3 of the [[analysis:course-w16|Leis book]]. Skip sections 3.4.3, 3.4.4, 3.4.5, 3.4.6, 3.4.7, 3.7. Skim section 3.6. | + | * (more technical background) read Chapter 3 of the [[analysis:course-w16|Leis book]]. Skip sections 3.4.3, 3.4.4, 3.4.5, 3.4.6, 3.4.7, 3.7. Skim section 3.6. |
==== Introductory remarks ==== | ==== Introductory remarks ==== | ||
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==== Motivating example: aliasing ==== | ==== Motivating example: aliasing ==== | ||
- | Before you begin, do a ''git pull'' from the course repository. Also, to reproduce the figures shown here, change the default font size (''set(0,'DefaultAxesFontSize',18)'' -- a good place to put this is in your path shortcut). | + | Let's start with an example that illustrates what can go wrong if you are not aware of some basic sampling theory ideas. To do so, we will first construct a 10Hz signal, sampled at 1000Hz (i.e. we are taking 1000 measurements per second). Recalling that the frequency //f// of a sine wave is given by $y = sin(2 \pi f t)$: |
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- | Let's start with an example that illustrates what can go wrong if you are not aware of some basic sampling theory ideas. To do so, we will first construct a 10Hz signal, sampled at 1000Hz. Recalling that the frequency //f// of a sine wave is given by $y = sin(2 \pi f t)$: | + | |
<code matlab> | <code matlab> |