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The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
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Convolution computations can be simplified by utilizing their inherent properties.
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Quality prediction using multiscale convolutional VAEs for thin plate parts

Xin Su1, Yichen Liu2, Ji Li3,4

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