Talk:Deconvolution/2D+

I got interested in higher dimensional deconvolution when contacted by someone about using it as a way of looking for trading indicators in financial time series. I set this task as an example of something that I'm speculating can be done well with functional and array processing languages, but only with difficulty otherwise, which I hope someone will weigh in to confirm or refute. In case anyone wants to know, consistent test data were generated partly by this higher dimensional convolution function, <lang Ursala>conv = +^|(~&x+,*DrlDSNiCK9xxSNiCK9K7iFS+ *)=>times+ **+ *K7|\x+ iota; * ! plus:-0</lang> invoked as (conv d)(h,f) with dimension d > 0 and conforming h and f. (This function essentially subsumes the Image convolution task as a special case with d = 2 and |h| = 3.) I suggest a development methodology based on warming up with Deconvolution/1D, then hand coding the solutions for the next few dimensions, and then looking for the pattern.

--Sluggo 03:24, 23 February 2010 (UTC)