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Pattern Recognition of Non-Stationary Time Series with Finite Length 被引量:3

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摘要 Statistical learning and recognition methods were used to extract the characteristics of size series measurements of cocoon filaments that are non-stationary in terms of mean and auto-covariance,by using the time varying parameter auto-regressive(TVPAR)model.After the system was taught to recognize the size data,the system correctly recognized the size of series of cocoon filaments as much as 96.95%of the time for a single series and 98.72%of the time for the mean of two series.The correct recognition rate was higher after suitable filtering.The theory and method can be used to analyze other types of non-stationary finite length time series.
作者 费万春 白伦
出处 《Tsinghua Science and Technology》 SCIE EI CAS 2006年第5期611-616,共6页 清华大学学报(自然科学版(英文版)
基金 Supported by the Natural Science Foundation of Jiangsu Province, China (No. L0313419913)
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