THIS is how you teach engineering. I'm actually motivated to learn now. A lot of professors just lecture in the wrong way... Thanks Tektronix. You've earned a like and subscribe.
i just wanted to make a simple tuner... why am I learning FFT, but actually out of all the articles I've read and tried to understand this is by far the most concise explanation.
Well, actually the FFT is an algorithm to perform a very fast DFT, which is the discrete fourier transformation, which is the descrete version of the fourier transformation, which in turn is, what you have explained in this video ;-) Just to be more precise with the terms FFT, DFT, and fourier transformation here.
That's a great explanation for non-mathematicians. Someone did a similar demo at Madley Satellite Station about 30 years ago for visitors. What BT were doing with FFT, TDR (like radar for the insides of wires), packet switching and Lee-Moore routing was mind-blowing to a layman - like detecting a broken line in India from England and instantly by-passing it by the cheapest route. And of course they were using your kit! FFT is everywhere now, in everyone's devices, even the noise-cancelling headphones on your kids' Christmas lists - and yet people still think maths isn't cool... Whaaat????
The title is misleading. This video has nothing to do with FFT (which is a particular algorithm of calculating the Discrete Fourier Transform quickly), but with its application to show the spectrum of a signal. The video shows how to view the spectrum on an oscilloscope, not how to do the FFT algorithm.
Thanks for the simple explanation of what fourier transforms are. All other videos on the subject just start of with a lot of math with the assumption I already know what it's use is.
OK video, but the title is misleading. You've explained the difference between a time and frequency signal domain and why it's useful. An FFT is an algorithm for calculating a DFT. Please consider changing the title of your video. Thanks.
Thanks! Great to see a simple demo of how to interpret harmonic distortion and how a bunch of sine waves can create different shaped waves ( at the appropriate intervals and amplitude, of course!)
Have you ever noticed how Newton's third law always seems to hold ? For every action , there is an opposite and equal reaction. In this case, the more sophisticated the equipment, the more ignorant the operator of the equipment ( i.e. the useless guy on the right, the one that obtained a PhD in Stupidity). Everything balances in life doesn't it ?
The explanation was great for explaining how to transform FFT back into the original signal, but not so much on transforming the waveform into FFT, as far as the math is concerned.
Yes I think that is the point. Any signal can be represented as a sum of sine waves with varying amplitude and frequency. On the scope, each peak on the bottom curve( frequency domain) is a frequency and amplitude of a sine wave. Successive peaks( sine waves) added together create the top wave. That is why a true sine wave has one peak in the frequency domain( bottom curve ). The later part of the video showed an issue with hardware or software used which had two peaks for a sine wave.
Hello friendly, I taste the video a lot. He wanted to know if they have an instruction manual where they explain to me as putting the oscilloscope graphics in an USB ( Tektronix ). I am accomplishing a project of the Doppler Effect and I wish to capture data when there is frequency drift in the spectrum analyzer.
Good demo of what a practical device does, it's in the "real" world, directly related to basic elements of material existence. Can this simple technical identification of phenomena be scaled to extended to the Quantum Fields Mechanism in Chemistry and Physics.
thanks guys! but imho you explained the ordinary fourier transformation and not the _fast_ fourier transformation which is fast, because of some - for me - unkown symmetry. i was looking for an explanation for this.
You're confusing mathematical operations with oscilloscopes, which possess an FFT button. They're explaining what it does. Tektronix are an oscilloscope manufacturer.
Wrong, the original definition of Fourier transform is defined over the full real number space. (In other words, infinitely long signals) In practice though, real-life signals are often sampled and always finite. That enables us to treat them as periodic signals(one period having the length of the full sampled signal) and to use FFT on them.
Miika Lehtimäki For Fourier series that is, not transforms, Fourier series are the mapping of the more general complex functions to real ones. See the T period in the expression of coefficient. The generalization of series is the Riemann integral. Can you prove that all functions in real function spaces , have an existent Fourier transform (what's the name of theorem or related one)
***** Fourier's transform works properly with finite energy signals and it's enough for engineering purposes. But you are right Fourier transform is very complex theme and it has roots in algebraic property of functional spaces.
xXxBladeStormxXx The transform is a distribution that maps from one domain "time" to "frequency". The expression of the signal in the frequency domain must exist and the integral must exist, not every function, can be represented in the integral form. Fourier series approximate the signal as the sum of sine waves in the time domain. Mathematically, in the fourier transform if the function "signal" isn't integrable and doesn't satisfy the dirichlet condition and bouded , it's fourier transform is undefined. Nonetheless, integrals can be approximated numerically, that's where the FTT comes in. I was speaking mathematically, but feel free to correct me if you still don't think it's correct.
***** I am a physics student, I use the Fourier Transform every day and even use the dirac delta version of it. I never once said all functions have a transform. Of course Dirichlet conditions need to be satisfied for convergence. I said: *" You can represent non periodic signals as well using the Fourier Transform"* Which was in reply to your statement that only periodic signals can be represented using sines. This is false. You can map non periodic signals as well using a continuous frequency distribution. I don't think you realize the difference between the *Fourier Series* and the *Fourier Transform*. The video is misleading as well since the FFT is an *algorithm* for calculating the DFT and what they are describing here is basically the Fourier Series.
I thought this was a really great video.
I found him
I agree
That ain’t the pouch buddy
THIS is how you teach engineering. I'm actually motivated to learn now. A lot of professors just lecture in the wrong way... Thanks Tektronix. You've earned a like and subscribe.
this is great. its like the world's most awkward fourier transform video.
hahahahahahahahahaha, right from the thubnail
i just wanted to make a simple tuner... why am I learning FFT, but actually out of all the articles I've read and tried to understand this is by far the most concise explanation.
Well, actually the FFT is an algorithm to perform a very fast DFT, which is the discrete fourier transformation, which is the descrete version of the fourier transformation, which in turn is, what you have explained in this video ;-) Just to be more precise with the terms FFT, DFT, and fourier transformation here.
ya i came here looking 4 fft stuff not an explanation of dft
@@sub-harmonik Well not the case for me, Seb-harmonik, Simon K has piqued my interest. I must discover what DFT is all about.
7 years later this is still an amazingly cool (in a way only nerds would understand) video.
That's a great explanation for non-mathematicians.
Someone did a similar demo at Madley Satellite Station about 30 years ago for visitors. What BT were doing with FFT, TDR (like radar for the insides of wires), packet switching and Lee-Moore routing was mind-blowing to a layman - like detecting a broken line in India from England and instantly by-passing it by the cheapest route. And of course they were using your kit!
FFT is everywhere now, in everyone's devices, even the noise-cancelling headphones on your kids' Christmas lists - and yet people still think maths isn't cool... Whaaat????
YES!
finally a demonstration that shows real-world examples. Thank you.
The title is misleading. This video has nothing to do with FFT (which is a particular algorithm of calculating the Discrete Fourier Transform quickly), but with its application to show the spectrum of a signal. The video shows how to view the spectrum on an oscilloscope, not how to do the FFT algorithm.
I appreciate the effort, but the second guy keeps interrupting the main guy that is talking all the time. So annoying!
+Ricardo Saavedra main guy should let him to speak. the video became more clear and energic.
I kinda get what he's trying to do but it's like he's trying too hard to be entertaining. He needs to know when to add a quip here and there.
I also have an Idea we can use FFT on both of the guys and can separate their voices.
xD
Well, what kind of behavior do you expect from a Burger King dropout ? He's as dumb as the day is long and couldn't pour water out of a boot.
Well done!
Simple, short and clear!
Thanks!
stop interfering the guy whose explaining. otherwise great stuff.
stop complaining over nothing. enjoy free knowledge
it's not nothing, someone interrupting an explanation makes hard for the knowledge to pass.
Fck. That guy is soooooooo annoying man. Hell.
@@thabonhlapo9323 I thought he is gay!!!
Thanks for the simple explanation of what fourier transforms are. All other videos on the subject just start of with a lot of math with the assumption I already know what it's use is.
this is the best video on fft in youtube.
Old video with golden explanation. Thanks
Mind blown. I mean it's *just* maths, but the very fact I understand this kind of maths is mind blowing.
Tony was like the unnecessary higher frequency sine wave riding on the main signal :D
THIS was the kind of channel I was looking for!
Well done guys you present it really well and make things easy to understand!
This video was one of the best explained about FFT. thank you
OK video, but the title is misleading. You've explained the difference between a time and frequency signal domain and why it's useful. An FFT is an algorithm for calculating a DFT. Please consider changing the title of your video. Thanks.
Thanks! Great to see a simple demo of how to interpret harmonic distortion and how a bunch of sine waves can create different shaped waves ( at the appropriate intervals and amplitude, of course!)
that's how you should teach students. great respect for you guys.
The best part of this tutorial is the responses about the useless guy on the right.....too funny, lmfao!!
Have you ever noticed how Newton's third law always seems to hold ? For every action , there is an opposite and equal reaction. In this case, the more sophisticated the equipment, the more ignorant the operator of the equipment ( i.e. the useless guy on the right, the one that obtained a PhD in Stupidity). Everything balances in life doesn't it ?
I didn't expect learning about FFTs to be so funny... I am pleasantly surprised
The explanation was great for explaining how to transform FFT back into the original signal, but not so much on transforming the waveform into FFT, as far as the math is concerned.
I wonder if they knew this would get half a million views on day, good job guys
Very simple.I wish if my teacher was like you guys.
Many thanks
I thought the video was great and a bit of humor breaks up the boring stuff. Good job lads.
Both dudes were on point. Fun and informative, great job!
Haven't done an FFT since college, but wish you could have been there 20 years ago to explain how they work.
One stares at the face of the other as the other speaks directly to the cam most of the time. lol
"Wow i cant believe that. That's excellent. That's really handy. Did you hear that? Wow."
It would only be entertaining if it was owen wilson
are you saying the top wave is the sum of all the waves at the bottom? I don't really understand.
Yes I think that is the point. Any signal can be represented as a sum of sine waves with varying amplitude and frequency. On the scope, each peak on the bottom curve( frequency domain) is a frequency and amplitude of a sine wave. Successive peaks( sine waves) added together create the top wave. That is why a true sine wave has one peak in the frequency domain( bottom curve ). The later part of the video showed an issue with hardware or software used which had two peaks for a sine wave.
Hello friendly, I taste the video a lot. He wanted to know if they have an instruction manual where they explain to me as putting the oscilloscope graphics in an USB ( Tektronix ). I am accomplishing a project of the Doppler Effect and I wish to capture data when there is frequency drift in the spectrum analyzer.
dear, i have a question for u. output of the iFFT process, is it modulated signal with high frequency? because i see it is multied with e^(-2piFt)
This was a great video! I'm programming an app dealing with sound waves. Same principles; and you explained them well!
Very good video, many thanks, my question is: this can be done with the Laplace transform ????
Good demo of what a practical device does, it's in the "real" world, directly related to basic elements of material existence.
Can this simple technical identification of phenomena be scaled to extended to the Quantum Fields Mechanism in Chemistry and Physics.
Fft never been so easy thank you very much guys !!
That sine turning into a square at 3:00 is pretty much what a tenor sax looks like on fft.
I liked the vid and the humor between u 2 made it more entertaining.. thanks!
To all you who don't like something... get a life
Where I could read open Audio processing journals?
Nice job guys. Thanks for the effort.
Great stuff guys. Thanks for the video. Learned something new today
thanks guys! but imho you explained the ordinary fourier transformation and not the _fast_ fourier transformation which is fast, because of some - for me - unkown symmetry. i was looking for an explanation for this.
Ditch the partner. Otherwise, it was a good video.
this is such an insightful video! thanks a lot!
"and this isn't just photoshop? this is real?" lol
FFT tutorials are at best with an unfocused camera.
Great video,
But why
Yea fft in music impartant noated😅
Thank you for explaining that so well!
I wish the teachers I have were as interesting and not boring as you guys are
+lefermier10 I think you forgot a comma. :)
Saved my life today. Jaja someone said ancient devices jajaja but those are exactly like the ones at my faculty so you really saved me :)
Excellent video!
I can't believe that it's so good wow
That was great. Thank you both.
@2:50 Not being annoying or anything, but sine typically starts at a value of zero.
you earned my subscription! 👏👍
This is a really good video.
Thanks for the free videos , ignore the idiots who are complaining
the left dude kept it interesting!
Can you FFT that guy's out? The real signal is coming from left.
can someone give the right guy a high five on the face
Thanks for saying what we were all thinking :)
You're confusing mathematical operations with oscilloscopes, which possess an FFT button. They're explaining what it does. Tektronix are an oscilloscope manufacturer.
Nice job. Thank you.
Amazing video
Good job guys, you`re explanations are really clear.
Good presentation, gets to the absolute basics of what an FFT IS.
Fuck this is so interesting if you love to play around with FM synthesizers.
没听懂英文，大概明白啥意思：应该是说矩形波可以是由很多种频率的波合成的，越接近矩形波频率的波的频率分量越大， 它们的频率能量是一个向下的曲线
Great Job! many thanks
Thanks guys !!
I thought this was going to explain how to calculate FFT, ie. the numerical method :( Instead it's about plain old Fourier Transforms...
Very good tutorial. Could have posted with good video resolution.
Dude Bro. You amazing!!
Great overhead tutorial. Thanks guys. This is wonderful for folks like me who want a quick, "What is this?" answer.
Hilarious and informative! Thanks, guys!
Thanks guys :)
I got squared up by Tony and Ian!
Nice Videos. Pls get an HD Camera (it'll help)
i can imagine the left guy playing tomba 2 and says "I would prefer if you can be quiet" to the other guy.
I loved it !
Thanks so much! great job and really helpful!
Thanks mate.
not every signal can be represented by bunch of sine waves, only periodic ones
Wrong, the original definition of Fourier transform is defined over the full real number space. (In other words, infinitely long signals) In practice though, real-life signals are often sampled and always finite. That enables us to treat them as periodic signals(one period having the length of the full sampled signal) and to use FFT on them.
Miika Lehtimäki
For Fourier series that is, not transforms, Fourier series are the mapping of the more general complex functions to real ones. See the T period in the expression of coefficient. The generalization of series is the Riemann integral. Can you prove that all functions in real function spaces , have an existent Fourier transform (what's the name of theorem or related one)
***** Fourier's transform works properly with finite energy signals and it's enough for engineering purposes. But you are right Fourier transform is very complex theme and it has roots in algebraic property of functional spaces.
xXxBladeStormxXx
The transform is a distribution that maps from one domain "time" to "frequency". The expression of the signal in the frequency domain must exist and the integral must exist, not every function, can be represented in the integral form. Fourier series approximate the signal as the sum of sine waves in the time domain. Mathematically, in the fourier transform if the function "signal" isn't integrable and doesn't satisfy the dirichlet condition and bouded , it's fourier transform is undefined. Nonetheless, integrals can be approximated numerically, that's where the FTT comes in. I was speaking mathematically, but feel free to correct me if you still don't think it's correct.
***** I am a physics student, I use the Fourier Transform every day and even use the dirac delta version of it. I never once said all functions have a transform. Of course Dirichlet conditions need to be satisfied for convergence.
I said: *" You can represent non periodic signals as well using the Fourier Transform"*
Which was in reply to your statement that only periodic signals can be represented using sines. This is false. You can map non periodic signals as well using a continuous frequency distribution.
I don't think you realize the difference between the *Fourier Series* and the *Fourier Transform*.
The video is misleading as well since the FFT is an *algorithm* for calculating the DFT and what they are describing here is basically the Fourier Series.
Does lithium work against spectrum analyzing personality disorder? :-o
nice
great Tutor !
Could you please upload tutorial about how to code FFT on arduino please and arduino coding in general ?
Cheers
It's weird putting a face to the logo on my machine
Why would anyone put up a video like this that IS OUT OF FOCUS?
super guys ! ;-)
thank you
I love you guys
mee too
crazy drawing skillz
The Best !!!!!!!
"You sure know your way around an oscilloscope" ... otherwise good explanation!
I like it. Thank!
Very good..
480p is so pre 2010. C'mon tektronix.