Комментарии:
Hi, I have a discrete voltage and current signal in time domain, what will be the formula to calculate the power using both voltage and current waveform in FFT method, it will be sum of the Individual powers in frequency domain or if you can put some insights or share your mail I can send you a email stating the exact problem. Thanks for the video.
Ответитьit is imposible to flow now if you do not have the version of your module (pip freeze) :(
ОтветитьWhat is the editero you are using?
ОтветитьThank you for these detail and very helpful videos
ОтветитьGreat work 👌👏👍
ОтветитьIf anyone is having trouble getting a symbolic result in the Part 2 section without a kernel crash, then try adding the following 'a' symbol:
a = smp.symbols('a', real = False)
x_FT = smp.integrate((1/T) * x *smp.exp(-a*t), (t,0,T)).subs([(a, 2*smp.pi*smp.I*fn)]).simplify()
This gave me something that looks different from the video's symbolic form, but it reproduces the numeric plot, so I'm happy with it!
Thank you!
ОтветитьVideo quality is worst.. Can't see what's types
ОтветитьThank you.
ОтветитьHi Mr Solver, thanks for your great effort to put this boring theory into interesting and visual python coding.
I tried out your codes everthing works except #2 Fourier Series (continuous time, discrete frequency). Your suggested solution is much appreciated
DFT formulas are a bit messed up. Useful vid :)
ОтветитьGreat content.
ОтветитьNot sure if the persistent integration issues with the upper integral limit `T' has to do with the many improvements to SymPy 1.11.1.
However, after lengthy consideration, here is the code that actually returns `x_FT` quickly and correctly without kernel crashes:
x_FT = sp.integrate(1/T * x*sp.exp(-2*sp.pi *sp.I *fn*t), (t, 0, sp.oo)).simplify() 🤓 Love your lectures. 😍
Great video
ОтветитьI subscribed before the singing, happy I subscribed. LOL awesome vid
ОтветитьHow about fractional fourier transform? Can you explain it?
Ответитьu bait me with the memes... and now im in image Fourier, pretty cool
ОтветитьAwesome lecture ever. Hello sir, can you make a tutorial on Fourier series of a triangular waveform?🙏🙏
ОтветитьD ear Mr. P Solver, can you tell us how to make spectral derivative in Python?
Ответитьcan you do for partial differential equations
ОтветитьThat rap is sick, man, keep on it.
ОтветитьWhat about amplitude and phase? And what about an entire spectrum of frequencies, instead of a basic ass sin function? This is so generic and superficial might as well just read the instructions on the np sp manuals SMH
ОтветитьGreat video thanks
Ответитьhey its great can you please help me in the code for how to fourier transform a signal which i have already plotted in python itself
ОтветитьMan! Where the hell have you been hiding from my recommendation list all this time? I have been looking for someone that would do EXACTLY your content for like ages! Thank you for all the time and effort to remove the fog from my eyes!
ОтветитьGreat Lecture!
Although as the frequency goes up, the sampling rate ought to be sufficiently INCREASED for good analog audio to be retrieved from a file with data recorded at, let's say 320bps,
so as to avoid aliasing as alluded to in cell 39. Should it not?
Doesn't look much like a simplification to me. Which ever way, one always gets this:
$\frac{1 - e^{- T k - 2 i \pi n}}{T k + 2 i \pi n}$
permission to learn sir
Ответитьhi, thank you so much for your informative videos, is it possible to do a video for solving the image MTF using py, thanks alot
ОтветитьWhere is dtft?
ОтветитьThank you. Have shared this video in our college Discord because our professor doesn't really explain things that well.
ОтветитьI want to fourier transform position wavefuntion to momentum for infinite square well and plot it. I am following this video where you transformed time to frequency. But in my case p (momentum) equals (iota)*(planck constant)*(partial by partial x). I am not sure hoew to define this. If you have sample of position to momentum fourier transform o anything to help, kindly tell me. Regards
ОтветитьHey Thankyou so much. Its too helpful. Stay blessed!
ОтветитьThanks for this video, I was struggling with my assignment, almost give up but here found a way to solve it! Very appreciated bro!
ОтветитьAdults with backwards cap from the hood. Not a good look. Mark Rober has made it his uniform and looks ludicrous. Like a teacher who wants to be "liked" by his students. Or an idiot with a kid show who wants to be cool. It isn't. Yo, lets rap on the relevant topics and express our feelings. Get down get up get up get up get down get up..... Truth to your mutha.
ОтветитьHey, Discovered your channel and have been hooked since. Just a small request. Would you mind zooming in just a little bit. The text is hard to read even at the highest res of 1080p.
Thanks.
I keep getting the following error:
"x_FT_integrand_real = lambda t: np.real(x(t, k)*np.exp(-2.0*np.pi*1j*f*t))
TypeError: 'Mul' object is not callable"
Why is this occurring, and how to get around it?
This is where repp'n and math collide
Ответитьmy thanks for this video, you saved me and my exam too! lol
ОтветитьIt'd be awesome if you could cover Gabor analysis or other time-frequency analysis methods.
ОтветитьGreat and hansome!
ОтветитьVery nice videos! Thank you so much.
ОтветитьPlease simulate random walk probably by python 🙏🙏🙏🙏
Ответить❤️❤️❤️❤️❤️
ОтветитьPlz share inverse fourrier transform system video too
ОтветитьMake video on epicycle
And converting any image to epicycle drawing
Are you planning on making a video about ipywidgets? After watching most of them I'm seriously considering getting [sympy + ipywidgets + numpy + numba + jupyter] as a free Mathematica-like environment.
Also, please, keep posting videos! They are very good and in time you will be in the 1M+ subs range!