Not being familiar with cosine distance, I found an NIST link: https://www.itl.nist.gov/div898/software/dataplot/refman2/au....

It seems like the main difference between convolution and cosine distance is the normalization. For example, if I associate vector A with the windowed data set and B with the cosine difference "kernel", then cosine difference will have a larger magnitude than a convolution for small A.

Cool idea. I plan to give it a whirl some day.