Using of Discrete Orthogonal Transforms for Convolution [pdf]
iris.elf.stuba.sk
iris.elf.stuba.sk
[A paper that as a lemma demonstrates the influence of boundary conditions on the use of discrete orthogonal transformations for fast convolution operations] https://scholar.google.com/citations?view_op=view_citation&h...
[accelerating convolution operations when a matrix factorization (SVD, DCT for jpeg, etc.) is already available]
https://scholar.google.com/citations?view_op=view_citation&h...
The paper might very well be produced by cribbing form other sources, I couldn't say -- but the central idea, that a convolution can be computed in some cases by methods with lower computational complexity than the product of the DFT, is interesting, I look forward to implementing it. :)
(And yeah, the product of two WHT transformed sequences does only need multiplication by +1 or -1...)
There was some buzz around convolution methods in the late 90s. Lake DSP had a notable patent which actually inspired some research. Most if not all of these methods now exist in Matlab and scipy.signal.convolve with far better documentation.
But I grow weary of random, crappy HN links like this one that really feel like some enthusiast did a Google search but didn't even read the paper.
Agreed, some context would be nice, and also agreed that it is poorly-written. I appreciate it much more when a paper I see on HN has some context from the submitter.