analysis:rhythms:step3

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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): |

- | + | ||

- | 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 $y = sin(2 \pi f t)$: |

- | | + | |

- | 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> |

analysis/rhythms/step3.1459280371.txt.gz · Last modified: 2018/07/07 10:19 (external edit)

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