Introduction to Circular Convolution and Filtering with the DFT

Relates the DTFT convolution-multiplication property to the DFT and the conditions under which multiplication of DFT coefficients corresponds to convolution in the time domain. Introduction to filtering by multiplication of DFT coefficients.

[@chandanjaiswal7011]

One of the most useful resources to learn Signal Processing .
Thanks a lot Sir .

[@paliendroom]

If only you would teach at my university. Thank you so much!

[@dallasjohnson6060]

My gosh I just found this...amazing. My DSP class is a killer

[@zz9758]

Thanks for the great lecture! If do H[n]* Sum{X[n-lN]}. this will convolute with all X[n-lN] ? The result shouldn't be the same as H[n]* X[n-lN] ?

[@allsignalprocessing]

Circular convolution is described in the next lecture in the DFT and Applications playlist. Somehow that temporarily got deleted from the playlist, but it is there again now.

[@mortezasjah6168]

Great explanation!

[@Capibara1]

Amazingly helpful, well done.

[@andrewdenterlein6447]

Thank you!

[@aothothien6621]

thank you. I have a problem.what the apply of the circular convulation? example: in the audio edited?

[@sacrusytong5640]

Great !..All your videos help me a lot to my DSP learning !
This video would be listed to which playlist?
Or there will be a playlist about Circular convolution ?

[@MrPicou51]

Great!

[@thevoid141]

I'm little confused at 8:14 . Convolution duration is (Mx + Mh - 2) or (Mx + Mh - 1) ?

[@SanduniPremaratne]

Number of samples. From zeroth to (Mx + Mh - 2)th. Note how Mx duration sequence has last sample at (Mx-1) and Mh long one has it at (Mh-1).