Tutorial: Convolution sum

Tks u

For given y(n) and h(n)
What will be input x(n)
??

Thank you so much for taking the time to help me with this!

Wow, so this is what my textbook was trying to explain to me? I I regret spending so much time trying to decipher that load of gibberish, when I could have just watched this video instead!

Thanks! Now that I have seen an example I understand it much better

Thank you so much. :)

Very nice

nice tutorial

I dont understand why its x[k]h[n-k] where does the -k come from why not +k?

Thank you so much! This was reallyyy helpfull!

elegant explanation! thank you

Great video this is way easier than the way I learned

OMG thank you so much for this vídeo. In 5 minutes I understood, in a much simpler way, the convolution summation. :D

how would you multiply it , without a shift?

This is a technique very different that what my professor taught us. A good shortcut, but I don't think my professor would be too impressed with it... Lol.

Taking my DSP Lectures this year and this helped me a lot! Too bad my professor cannot really explain this well. Thank you very much Rose-Hulman. Cheers from the Philippines

helps a lot! thx 

Thank you so much for those videos! I passed my exam only thanks to those (it's not really my field as I study IT)! It also helped a lot of my friends.

good video, thank you

right picture: delta or h [n-5] ?

Thank you so much 

Reply to Trần Hồng Phúc: The two formulas are equivalent: your equation (Xmax+Hmax) - (Xmin+Hmin)+1 = (Xmax-Xmin) + (Hmax-Hmin) +1 = (Xmax-Xmin+1) + (Hmax-Hmin+1) - 1 = Xlength + Ylength - 1 = equation in video.

This video solved my 1 year old problem

Your tutorial is very understandable and usefull,but, your fomular for calculating the length of y is only right in this case, the others will be wrong. Could you take look again?

Generally, the length of y =(max index x+max index h) - (min index x+min index h) +1

The method shown here is based on what physically happens with the system. Each input sample triggers its own scaled and shifted (delayed) impulse response, and these are all added together to form the output. Look particularly at 7:42, and you can see the effect of the delay in the argument for h, it appears as h[n-1]. The other method that you are thinking about ("flip and slide") is based on the convolution sum equation; the delay shows up as negated time index (k) and that's why h must flip.

Is there a reason that you did not need to flip the LTI system (H) due to the negative sign infron of the k in h(n-k) ??? Please let me know as I am confused

it was really easy to understand, besides, the method introduced in the example is really convenient.

Wow. Discrete convolution is a lot simpler than continuous.

Amazing video! Was of tremendous help! Thank you :)

Chuck Norris is drawing this graphics.

Thanks very useful XD

nice video...good job helped me a lot