Results 21 to 30 of about 655,816 (301)
Hexadecimal Aggregate Approximation Representation and Classification of Time Series Data
Algorithms, 2021 Time series data are widely found in finance, health, environmental, social, mobile and other fields. A large amount of time series data has been produced due to the general use of smartphones, various sensors, RFID and other internet devices. How a time
Zhenwen He +3 more
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LBP4MTS: Local Binary Pattern-Based Unsupervised Representation Learning of Multivariate Time Series
IEEE Access, 2023 Representation learning of multivariate time series is a crucial and complex task that offers valuable insights for numerous applications, including time series classification, trend analysis, and regression.
Chengyang Ye, Qiang Ma
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Time Series Piecewise Linear Representation Method Based on First-order Filtering [PDF]
Jisuanji gongcheng, 2016 For the time series whose slope fluctuation frequency is relatively fierce,time series piecewise algorithm with edge point extraction based on slope is easy to fall into local optimum.It cannot keep the overall features of original time series.For this ...
LIN Yi,WANG Zhibo
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Abridged Symbolic Representation of Time Series for Clustering
Acta Universitatis Lodziensis. Folia Oeconomica, 2019 In recent years a couple of methods aimed at time series symbolic representation have been introduced or developed. This activity is mainly justified by practical considerations such memory savings or fast data base searching.
Jerzy Korzeniewski
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Piecewise Trend Approximation: A Ratio-Based Time Series Representation
Abstract and Applied Analysis, 2013 A time series representation, piecewise trend approximation (PTA), is proposed to improve efficiency of time series data mining in high dimensional large databases.
Jingpei Dan +3 more
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Le pouvoir de la fiction télévisée d’un point de vue temporel
Communication, 2017 Whoever controls time exerts power, but the contemporary fragmentation of time makes it more difficult to control. Hence a sense of loss. The French short fiction television series Bref, beyond its comic content, offers the visceral experience of re ...
Jean-Bernard Cheymol
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Yet Another Compact Time Series Data Representation Using CBOR Templates (YACTS)
Sensors, 2023 The Internet of Things (IoT) technology is growing rapidly, while the IoT devices are being deployed massively. However, interoperability with information systems remains a major challenge for this accelerated device deployment.
Sebastian Molina Araque +4 more
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Decoupling Local and Global Representations of Time Series
CoRR, 2022 Real-world time series data are often generated from several sources of variation. Learning representations that capture the factors contributing to this variability enables a better understanding of the data via its underlying generative process and improves performance on downstream machine learning tasks.
Sana Tonekaboni +4 more
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Self-Distilled Representation Learning for Time Series
CoRR, 2023 Self-supervised learning for time-series data holds potential similar to that recently unleashed in Natural Language Processing and Computer Vision. While most existing works in this area focus on contrastive learning, we propose a conceptually simple yet powerful non-contrastive approach, based on the data2vec self-distillation framework.
Felix Pieper +4 more
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A Novel Segmentation and Representation Approach for Streaming Time Series
IEEE Access, 2019 Along with the coming of Internet of Everything era, massive numbers of pervasive connected devices in various fields are continuously producing oceans of time series stream data.
Yupeng Hu +4 more
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