Distance- and Momentum-Based Symbolic Aggregate Approximation for Highly Imbalanced Classification [PDF]
Sensors, 2022 Time-series representation is the most important task in time-series analysis. One of the most widely employed time-series representation method is symbolic aggregate approximation (SAX), which converts the results from piecewise aggregate approximation ...
Dong-Hyuk Yang, Yong-Shin Kang
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Activity Identification, Classification, and Representation of Wheelchair Sport Court Tasks: A Method Proposal [PDF]
Methods and ProtocolsBackground: Monitoring player mobility in wheelchair sports is crucial for helping coaches understand activity dynamics and optimize training programs.
Mathieu Deves +6 more
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Anomaly detection in ECG based on trend symbolic aggregate approximation
Mathematical Biosciences and Engineering, 2019 ECG anomaly detection is a necessary approach to detect disease Electrocardiography(ECG) signals before the detail diagnosis process in medical field to gauge the health of the human heart.
Chunkai Zhang +3 more
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Using symbolic aggregate approximation (SAX) to visualize activity transitions among older adults. [PDF]
Physiol Meas, 2016 The objective of this analysis was to apply symbolic aggregate approximation (SAX) time-series analysis to accelerometer data for activity pattern visualization stratified by self-reported mobility difficulty. A total of 2393 (71.6 ± 7.9 years old) participants wore an accelerometer on the hip (4 + d; 10 + h) during the national health and ...
Wanigatunga AA +3 more
europepmc +4 more sources
A comparative study of symbolic aggregate approximation and topological data analysis
Quantitative Finance and EconomicsThe movement of stocks is often perceived as random due to the complex interactions between different stocks and the inherently chaotic nature of the market.
Fredrik Hobbelhagen, Ioannis Diamantis
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An ICEEMDAN and SAX-based method for determining English reading comprehension status using functional near-infrared spectroscopy signals. [PDF]
PLoS ONEAccurate, rapid, and objective reading comprehension assessments, which are critical in both daily and educational lives, can be effectively conducted using brain signals.
Ural Akincioglu +3 more
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Towards a faster symbolic aggregate approximation method [PDF]
Proceedings of the 5th International Conference on Software and Data Technologies, 2010 The similarity search problem is one of the main problems in time series data mining. Traditionally, this problem was tackled by sequentially comparing the given query against all the time series in the database, and returning all the time series that are within a predetermined threshold of that query.
Muhammad Fuad, Muhammad Marwan +1 more
openaire +5 more sources
Making Time Series Embeddings More Interpretable in Deep Learning
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 With the success of language models in deep learning, multiple new time series embeddings have been proposed. However, the interpretability of those representations is often still lacking compared to word embeddings. This paper tackles this issue, aiming
Leonid Schwenke, Martin Atzmueller
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Compositional Algorithms for Succinct Safety Games [PDF]
, 2015 We study the synthesis of circuits for succinct safety specifications given in the AIG format. We show how AIG safety specifications can be decomposed automatically into sub specifications.
Brenguier, Romain +3 more
core +9 more sources
Transitional SAX Representation for Knowledge Discovery for Time Series
Applied Sciences, 2020 Numerous dimensionality-reducing representations of time series have been proposed in data mining and have proved to be useful, especially in handling a high volume of time series data.
Kiburm Song, Minho Ryu, Kichun Lee
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