Convolution in the time domain

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[romanvereb]

Mike X Cohen - the unsung hero of our age

[weilawei]

Super clear explanation, very intuitive. Thank you.

[violincrafter]

Wings of convolution: a good band name

[me-ourf]

Doesn't using kernel for convolutional which have some value for n= negative violates causality ?
In the first case, wavelet was mirrored so h(-n), and h(n)/wavelet-kernel in that case was not causal.
However, in case of second type of convolution where convolution result is longer than signal, causality condition on the convolution kernel was satisfied I guess.
?

[ormedanim]

you lost me at God's perspective, now I'm flipping (out) instead of the kernel :D But I am very thankful for all the videos and the ANTS book <3

[MrPabloguida]

Is it fair to say that the result signal, even after cutting out the wings, will still be "contaminated" by the zero padding for at least another half kernel length, which would be when it start having a pure and clean signal/kernel convolution? Does it make sense?

[jesusdanielolivaresfiguero]

Is there a way to buy your Analyzing Neural Time Series Data book on credit for monthly payments?

[brixomatic]

Wouldn't the convolution it be a better representation of the signal, if you could wrap around the edges of the signal?
I.e. you'd start the kernel's mid point at the start of the signal and take the left half of the kernel from the right side of the signal and if the kernel exceeds the right bounds, take the data from the start of the signal? This way your convolution would have the same length as the signal, but operate only on the signal's data and not sneak in zeroes that have no meaning and pollute the results.

[bokkieyeung]

I'm wondering why not aligning the center of the kernel with the edge of the signal (still need zero-padding, but less extra zeros) so that we can get the result with exact same length as the original signal, thus no need to cut off the "wings"?

[hurstcycles]

If the kernel is a morlet wavelet (formed by combining a constant sine wave and gaussian) and symetrical around the mid point, flipping the kernel is not necessary, is that accurate? Thanks for the great video

[helenzhou]

This video is super helpful, thank you so much!

[RenanAlvess]

congratulations for explanation, was very enlightening for me

[prempant]

How do you decide what sort of kernel to use?