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Classification of Short Time Series in Early Parkinson’s Disease With Deep Learning of Fuzzy Recurrence Plots 被引量:9
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作者 Tuan D.Pham Karin Wardell +1 位作者 Anders Eklund Goran Salerud 《IEEE/CAA Journal of Automatica Sinica》 EI CSCD 2019年第6期1306-1317,共12页
There are many techniques using sensors and wearable devices for detecting and monitoring patients with Parkinson’s disease(PD).A recent development is the utilization of human interaction with computer keyboards for... There are many techniques using sensors and wearable devices for detecting and monitoring patients with Parkinson’s disease(PD).A recent development is the utilization of human interaction with computer keyboards for analyzing and identifying motor signs in the early stages of the disease.Current designs for classification of time series of computer-key hold durations recorded from healthy control and PD subjects require the time series of length to be considerably long.With an attempt to avoid discomfort to participants in performing long physical tasks for data recording,this paper introduces the use of fuzzy recurrence plots of very short time series as input data for the machine training and classification with long short-term memory(LSTM)neural networks.Being an original approach that is able to both significantly increase the feature dimensions and provides the property of deterministic dynamical systems of very short time series for information processing carried out by an LSTM layer architecture,fuzzy recurrence plots provide promising results and outperform the direct input of the time series for the classification of healthy control and early PD subjects. 展开更多
关键词 Deep learning early Parkinson’s disease(PD) fuzzy recurrence plots long short-term memory(LSTM) neural networks pattern classification short time series
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Discussion on the paper “Analyzing short time series data from periodically fluctuating rodent populations by threshold models: A nearestblock bootstrap approach”
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作者 LI W.K.& LI GuoDong Department of statistics and Actuarial Science,University of Hong Kong,Pokfulam Road,Hong Kong,China 《Science China Mathematics》 SCIE 2009年第6期1109-1110,共2页
The authors are to be congratulated for an innovative paper in terms of both modelling methodology and subject matter significance. The analysis of short time series is known to be
关键词 time Discussion on the paper A nearestblock bootstrap approach Analyzing short time series data from periodically fluctuating rodent populations by threshold models GARCH data
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Discussion on the paper “Analyzing short time series data from periodically fluctuating rodent populations by threshold models: A nearestblock bootstrap approach”
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作者 HALL Peter 《Science China Mathematics》 SCIE 2009年第6期1107-1108,共2页
This is a very attractive article. It combines fascinating new methodology with a most interesting dataset, and a highly motivating presentation. However, despite the many
关键词 time A nearestblock bootstrap approach Analyzing short time series data from periodically fluctuating rodent populations by threshold models Discussion on the paper data
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Empirical orthogonal function analysis of short time series of sectional data in the tropical western Pacific
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作者 Liu Baiqiao (National Marine Data and information ffervice, State oceanic Administrator, Tianjin 300171, China) 《Acta Oceanologica Sinica》 SCIE CAS CSCD 1996年第3期307-321,共15页
In this paper,some short time series of pnserved data pm sectopm 18°20′N in the tropical western Pacificwere reorganized to give mixed depth-time series,and processed by means of means of empirical orthogonal fo... In this paper,some short time series of pnserved data pm sectopm 18°20′N in the tropical western Pacificwere reorganized to give mixed depth-time series,and processed by means of means of empirical orthogonal fonction analysis. It is indicated that the original form of element distribution could be obtained by linear combination of several main canonical distribution functions, and the intrinsic structure of element distribution on a certain section and its variation propertiescould be reveled by canonical distribution function and profiles in corresponding periods. 展开更多
关键词 The tropical western Pacific short time series empirical orthogonal function
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