To my mind, the key questions in general here are whether the problem needs parallel processing at scale and whether map/reduce can be profitably applied to the problem.
FIR and IIR input filters for time-series are definitely important in some domains and for extremely large time series or large filters, these may actually benefit from map-reduce implementation. So the next question is whether you would have benefited by having these operations operate in parallel. I definitely can say that all of the time series problems I have had to deal with had very moderate scale and thus didn't really need any subsequent processing. You sound like you have had a different experience. If so, then please do implement these since we would all learn from your experience. On the other hand, implementing something just because somebody might someday find it useful would not be very helpful. The biggest reason for this is that if you don't feel the pain already, you probably can't guess what pains somebody else will feel when they need this capability. On 2/17/08 2:03 PM, "Simone Gianni" <[EMAIL PROTECTED]> wrote: > Hi all, > are DSP filters (FIR,IIR etc..) something useful for this project? > Digital Signal Processing is used in some fields of Machine Learning, > mainly to pre-process or to filter data before ingestion in Machine > Learning algorithms. > > Simone
