do you mean W_N = exp(-j2 pi/N)? If so, Euler's formula is the easiest way to do this. It says exp(-j2 pi/N) = cos(2 pi/N) + j sin(2 pi/N). I have lectures in the Background Material playlist that discusses complex numbers (Complex Numbers Review) and complex sinusoids (Complex Sinusoids Review) - those may be helpful. Sorry TH-cam won't let me leave links for those in comments, so you have to search my channel.
This is a rutine which can be incorporated into researching or studying. Great presentation how the Discrete Fourier Transform is set put as a matrix operation. Like how you imply because even it is 21th century if large amounts of data are to be processed, this can become incordinate, even for computer. For example in oreder to simplify the mass matrix formulation and reduce computing time for beam or squre plate vibration. 👍🤌
would you please elaborate the difference between 'n' and 'k' int that analysis equation? plus the inverse W matrix only seems to be the conjugate of the W and not the transpose of it.
I know you asked this 5 years ago but im gonna respond anyways lol. k is the frequency bin and n is the time domain sample. Soif you have 128 samples in the time domain n = 120 is the 120th sample. You're going to have the same amount of frequency bins as time domain samples, but the actual frequency spacing between bins depends on the length of your sample as well as the sampling frequency. I doubt you care anymore tho 💀
Thank you so much for your teaching :D. This lecture ended my two-year long journey on Fourier series...
spiegazione eccellente. Grazie mille prof
Hey Barry, could you please provide a brief explanation on how to calculate the real and imaginary part of a particular W complex exponential
Thanks Man, Could you do more of these?
do you mean W_N = exp(-j2 pi/N)? If so, Euler's formula is the easiest way to do this. It says exp(-j2 pi/N) = cos(2 pi/N) + j sin(2 pi/N). I have lectures in the Background Material playlist that discusses complex numbers (Complex Numbers Review) and complex sinusoids (Complex Sinusoids Review) - those may be helpful. Sorry TH-cam won't let me leave links for those in comments, so you have to search my channel.
Thank you very much
Excuse me, do you know anything about the transformed taylor-Fourier?
DTFT?
This is a rutine which can be incorporated into researching or studying. Great presentation how the Discrete Fourier Transform is set put as a matrix operation. Like how you imply because even it is 21th century if large amounts of data are to be processed, this can become incordinate, even for computer. For example in oreder to simplify the mass matrix formulation and reduce computing time for beam or squre plate vibration. 👍🤌
sir, can u explain how to solve 2D DFT image with sum
Shouldn't the basis vectors start from W0? Because when l = 1, what we get as W(l) is the second column of the inverse matrix.
Many Thx, your video solved my problem.
would you please elaborate the difference between 'n' and 'k' int that analysis equation? plus the inverse W matrix only seems to be the conjugate of the W and not the transpose of it.
I know you asked this 5 years ago but im gonna respond anyways lol. k is the frequency bin and n is the time domain sample. Soif you have 128 samples in the time domain n = 120 is the 120th sample. You're going to have the same amount of frequency bins as time domain samples, but the actual frequency spacing between bins depends on the length of your sample as well as the sampling frequency. I doubt you care anymore tho 💀
Still.. thankyou 😂
Thanks, very much
Thanks man
Tq sir