I have to make a primitive pattern identifier..
There is a list of values the values are but most of them are insignificant random of noice of various magnitude.
Like this for example 101, 203, 321, 45, 67, 156 etc.
or for example 521, 313, 31, 145, 167, 56 etc.

Among this values are "islands" of values where the values are much higher then the surrounding noice. In this fashion:

101, 203, 321, 45, 67, 156, 203, 502, 899, 2003, 5007, 8020, 7301, 5030, 3045, 1243, 567, 321, 234, 45, 123 453 etc..

I have to make some algorithm to identify this "islands" which stick up from the surrounding noice. The noice could be at different levels so I can not just sum up values over a general noice level.v Do you have any ideas how to do this in the best way? I would be very happy if you knew about a book about how to do similar things?

Than you very much for your help.

2006-04-27 Retitled by GrandFather, as per Monastery guidelines
Original title: 'primitive pattern identifier'

In reply to How do I find peaks in noisy data? by tamaguchi

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