yes, look up linear convolution via circular convolution, it involves zero padding both signals such that they have length n + m - 1, where m and n are the lengths of the two signals. the case in this example is that both the signals aren't of the same length, and as we have to take the N point DFT of both, we sufficiently zero pad the shorter duration signal.
can you please explain how H(3) is the complex conjugate of H(1), from what I learned about the twiddle factor, it should be that H(3) = -H(1). could someone please clarify
the title literally says "using the DFT method", ofc there are other ways to solve this problem, the fact that the matrix method is easier may mean that that is a more covered topic on youtube. what if in your exam youre asked to use the DFT property of circular convolution? youll get exactly zero marks if you solve it in the time domain.
OMG, this is brilliant
very clear explanation sir
thank u
very clear explanation sis
thank u
Can you perform Linear convolution with this?
What if the length of both signals are not equal?
yes, look up linear convolution via circular convolution, it involves zero padding both signals such that they have length n + m - 1, where m and n are the lengths of the two signals. the case in this example is that both the signals aren't of the same length, and as we have to take the N point DFT of both, we sufficiently zero pad the shorter duration signal.
Thank you so much Sir 👌
can you please explain how H(3) is the complex conjugate of H(1), from what I learned about the twiddle factor, it should be that H(3) = -H(1).
could someone please clarify
Did you find the answer ? I am also confused
Property of dft
it's much easier by matrix method
the title literally says "using the DFT method", ofc there are other ways to solve this problem, the fact that the matrix method is easier may mean that that is a more covered topic on youtube. what if in your exam youre asked to use the DFT property of circular convolution? youll get exactly zero marks if you solve it in the time domain.