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New classification methods of branching patterns
Author(s) -
Pelt J.,
Verwer R. W. H.
Publication year - 1984
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.1984.tb02543.x
Subject(s) - branching (polymer chemistry) , pattern recognition (psychology) , computer science , artificial intelligence , chemistry , organic chemistry
SUMMARY Binary branching patterns are described in this paper by their topological structure. The statistical properties of these structures appear to be highly dependent on their growth patterns. As such, observed trees may be used for testing growth models. This paper describes three options in the construction of frequency distributions of topological parameters and their corresponding probability distributions, arising from the terminal and segmental growth models. The construction of these distributions makes the analysis of observed tree structures possible in those experimental conditions where small numbers of observations or differing sizes of trees would form serious obstacles to alternative analytical procedures.