The Journal of Silk Science and Technology of Japan
Online ISSN : 1881-1698
Print ISSN : 1880-8204
ISSN-L : 1880-8204
Pattern Recognition Method for Size Series of Cocoon Filament
Wanchun FEILun BAI
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2005 Volume 14 Pages 81-85


In order to categorize size series of cocoon filament (SSCF), which are non-stationary time series with finite length in terms of mean and auto-covariance, by means of the time varying parameter auto-regressive (TVPAR) model theory, statistical methods of learning and recognition were used to extract the characteristics of size series of cocoon filament. Through learning the size series, using closed data, the rates of correct recognizing which of two cocoon categories a given size series of cocoon filaments belongs to were 96.95% and 98.72% for a single series and the mean of two series, respectively. The rate of correct recognition was higher after suitable filtering. The theory and method can be used to analyze other types of non-stationary time series with finite length.

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© 2005 by The Japanese Society of Silk Science and Technology
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