Signal Processing Tutorial: Sampling/Anti-Aliasing or the Nyquist Sampling Theorem

http://www.FreedomUniversity.TV. These videos are part of a series of engineering videos on Nyquist sampling Theorem or concepts of the Nyquist Frequency or Nyquist Rate. The Shannon Theorem is a difficult concept for most students. When viewed from the frequency domain you will see that amplitude modulation can be viewed as a special case of sampling. These videos are in pre-production and will be replaced with the final versions.

Category:

Education

Tags:

• digital
• communications
• sampling
• convolution
• laplace
• transform
• nyquist
• frequency
• time
• domain
• amplitude
• modulation
• matlab
• rate

[KaslarProductions]

sound engineering with annoying audio..... Ironic I must say....

[drjctu]

@KaslarProductions You're right. I tried the mouse click feature for this video using the Camtasia software. This is the only video with this annoying clicking sound. There are other videos in sampling. When I have time, I'll try to do this one again without the clicks. Dr J.

[lastsamuri]

The tutorial is quite good and informative, however the powerpoint animation scheme with a strange sound is really annoying. :(

If possible please remove the sound.

[drjctu]

Thanks for the feedback. This is one of my first videos and I did not use the clicking feature. There are other videos on this that describes the sampling concept. If you can't find them let me know. Dr J

[iraslav]

nice animation

[spartan1081990]

so is this video game aa? but represented mathematically? how beautiful.

[richriscy]

3 years is a long time to be in pre-production for a YouTube vid!  Are you Spielberg? You're clearly not his sound recordist!

[kshep1983]

The thing to do is to take a fourier transform of the audio file and figure out the frequency spectrum of the annoying clicking. Then, make a software filter that knocks it out.

[69erthx1138]

@bitchbitchbaconbacon Think of breaking up a signal in time domain into discrete parts (a sum of impulse or detla functions). Each part you sample has a characteristic spectral value (a width or grouping of frequencies) associated with it. As you let the number of samples increase (theoretically toward infinity), the spectral density of the original signal is recovered. The multiple spectra are akin to an infinite series that converge to the value of some function (original signal).

[69erthx1138]

@KaslarProductions Too bad also, looks like a good video.

[KaslarProductions]

@drjctu

lol....

no worries =D

[attila009]

Maybe nice explanation, but quietly voice and much louder clicking noice is impossible to watch!!!

[MikeHall683]

the clicking noise hurts my ears!! nice tut though!