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OverviewTime-series classification is the common theoretical background of many recognition tasks performed by computers, such as handwriting recognition, speech recognition or detection of abnormalities in electrocardiograph signals. In this book, the state-of-the-art in time-series classification is surveyed and five new techniques are presented. Four out of them aim at making the recognition more accurate, while the proposed instance-selection algorithm speeds up time-series classification. Besides time-series classification tasks, potential applications of the proposed techniques include problems from various domains, e.g. web science or medicine. Full Product DetailsAuthor: Krisztian BuzaPublisher: Peter Lang AG Imprint: Peter Lang AG Edition: New edition Volume: 45 Weight: 0.310kg ISBN: 9783631630853ISBN 10: 3631630859 Pages: 144 Publication Date: 25 November 2011 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Out of stock  The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available. Table of ContentsContents: Survey of the state-of-the-art in time-series classification - Individual Quality Estimation - Speeding-up time series classification using instance selection - GRAMOFON, a graph-based ensemble framework - Fusion of time series distance measures - Discovery of recurrent patterns (motifs) in time series - Applications to electrocardiograph signals and web-science problems.ReviewsAuthor InformationKrisztian Antal Buza obtained his diploma at the Budapest University of Technology and Economics in 2007, and his PhD at the University of Hildesheim in 2011. His work on time-series classification was honored by the Best Paper Award at the renowned conference on Computational Science and Engineering of the Institute of Electrical and Electronics Engineers (IEEE) in 2010. Tab Content 6Author Website:Countries AvailableAll regions |
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