Talk:Spectral power distribution
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editas a phd, molecular biology, who often works with % transmittance and absorbance - the intro, as is common with technical articles on wiki, is way, way, way to complex. If you are really an expert, you should be able to capture the essence without the math; you can bring in the math later, but right now the article is basically incomprehensible to someone who is not already an expert (sorry) Ps: I no longer contribute to wiki, because of the copyright policy, which allows for profits to take wiki articles and sell them. I don't mind if a nonprofit takes my hardwork and makes it available, but I will be dam*** if I will let some for profit entity make moeny off of my labor; thats crazy and I suggest all wiki people think about thatCinnamon colbert (talk) 22:36, 20 September 2011 (UTC)
- Agreed. Feel free to try your hand at a longer and less technical description. As for sales and derivatives of Wikipedia material: Any content which cannot be included in for-profit enterprises, broadly conceived, is not really “free”. The much more important usage restriction is copyleft, which demands that any rights given to one reader/viewer are likewise guaranteed in derivative works. See http://freedomdefined.org/Licenses/NC. –jacobolus (t) 02:23, 21 September 2011 (UTC)
Not technical enough for me ...
editI wanted to find a sound mathematical definition of "color", but not in the sense of "the color we perceive", but what actually arrives at our eye. After quite some searching I came here, and I think it is what I was looking for. But still ... As far as I understand, there exists light with a discrete spectrum, and I don't see how the definition given here (using a square integrable function) would work for that. Should it not be something like a distribution (or generalized function)? --129.132.146.194 (talk) 14:00, 7 December 2012 (UTC)
- The idea of a distribution (in the sense of Laurent Schwartz) treatment does not really work. The difficulty of treating both the line spectrum and the continuous spectrum together is solved by using the spectral measure or its equivalent, the spectral cumulative distribution function.66.167.204.242 (talk) 17:10, 18 April 2014 (UTC)
Title and "not to be confused with"
editI hastily concede there is no good solution to this problem. But it is a problem, that the same phrase, or more often with a slight change in order, "power spectral distribution", is more widely used in the fields of statistics and statistical signal processing, to mean the related but different concept of the cumulative distribution function of the power spectrum. In fact the terminology is not completely standardised. The choices of titles for this article and its related article spectral density unfortunately create the impression that the difference is somehow allied with the difference between a density and a distribution, but this is not true, very misleading in fact. Both notions of power spectrum, the one used here and the one used in statistics, possess a distribution version and a density version. In each notion, the distinction between density and distribution is the same as the distinction between a probability distribution and a probability density, and is thus a distinction *within* the concept, not a distinction *between* these two articles. So I added a slight explanation and cross-reference in the top of this article, to counteract the misleading impression of "not to be confused with spectral density".66.167.204.242 (talk) 18:10, 19 April 2014 (UTC)
External links modified (January 2018)
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