Bag of recurrence patterns representation for time-series classification
نویسندگان
چکیده
منابع مشابه
Bag-of-Words Representation for Biomedical Time Series Classification
Automatic analysis of biomedical time series such as electroencephalogram (EEG) and electrocardiographic (ECG) signals has attracted great interest in the community of biomedical engineering due to its important applications in medicine. In this work, a simple yet effective bag-of-words representation that is able to capture both local and global structure similarity information is proposed for...
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Time series classification is an application of particular interest with the increase of data to monitor. Classical techniques for time series classification rely on point-to-point distances. Recently, Bag-ofWords approaches have been used in this context. Words are quantized versions of simple features extracted from sliding windows. The SIFT framework has proved efficient for image classifica...
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This chapter studies the problem of time-series classification and presents an overview of recent developments in the area of feature extraction and information fusion. In particular, a recently proposed feature extraction algorithm, namely symbolic dynamic filtering (SDF), is reviewed. The SDF algorithm generates low-dimensional feature vectors using probabilistic finite state automata that ar...
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Article history: Received 12 February 2014 Received in revised form 13 August 2014 Accepted 29 August 2014 Available online 8 September 2014
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ژورنال
عنوان ژورنال: Pattern Analysis and Applications
سال: 2018
ISSN: 1433-7541,1433-755X
DOI: 10.1007/s10044-018-0703-6