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Titlebook: Nonlinear Analysis of Physiological Data; H. Kantz,J. Kurths,G. Mayer-Kress Conference proceedings 1998 Springer-Verlag Berlin Heidelberg

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發(fā)表于 2025-3-21 19:53:33 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Nonlinear Analysis of Physiological Data
編輯H. Kantz,J. Kurths,G. Mayer-Kress
視頻videohttp://file.papertrans.cn/668/667330/667330.mp4
概述Nonlinear methods to analyze predical data and their implementation in computer-aided diagnostics are very new but of growing importance despite their inherent complexity.
圖書(shū)封面Titlebook: Nonlinear Analysis of Physiological Data;  H. Kantz,J. Kurths,G. Mayer-Kress Conference proceedings 1998 Springer-Verlag Berlin Heidelberg
描述This book is more than a standard proceedings volume, although it is an almost direct result of the workshop on "Nonlinear Analysis of Physiologi- cal Time Series" held in Freital near Dresden, Germany, in October 1995. The idea of the meeting was, as for previous meetings devoted to related topics, such as the conference on dynamical diseases held near Montreal in February 1994 (see CHAOS Vol. 5(1), 1995), to bring together experts on the techniques of nonlinear analysis and the theory of chaos and applicants from the most fascinating field where such methods could potentially be useful: the life sciences. The former group consisted mainly of physicists and mathe- maticians, the latter was represented by physiologists and medical researchers and practitioners. Many aspects of this workshop were unusual and not previously expe- rienced. Also, the hosting institution, the Max Planck Institute for Physics of Complex Systems (MPIPKS), at this time was brand new. The organiz- ers‘ rather unconventional intention was to bring specialists of both groups together to really work together. Therefore, there was an excessive availabil- ity of computers and the possibility to numerically study
出版日期Conference proceedings 1998
關(guān)鍵詞Master Patient Index; bifurcation; classification; development; diagnostics; modeling; perception
版次1
doihttps://doi.org/10.1007/978-3-642-71949-3
isbn_softcover978-3-642-71951-6
isbn_ebook978-3-642-71949-3
copyrightSpringer-Verlag Berlin Heidelberg 1998
The information of publication is updating

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pite their inherent complexity.This book is more than a standard proceedings volume, although it is an almost direct result of the workshop on "Nonlinear Analysis of Physiologi- cal Time Series" held in Freital near Dresden, Germany, in October 1995. The idea of the meeting was, as for previous meet
板凳
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Ranking and Entropy Estimation in Nonlinear Time Series Analysisstatistical dependences in scalar or multivariate time series. A fast algorithm for its estimation is described in detail which essentially profits from ranking of the scalar components of the time series.
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Analyzing Spatio-Temporal Patterns of Complex Systems a detailed documentation of spatio-temporal processes in biological systems. Therefore, it is of extreme importance to develop methods which allow for a characterization and classification of spatio-temporal processes with special emphasis on medical applications.
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Are R-R-Intervals Data Appropriate to Study the Dynamics of Heart?onsequently, it seems that recovery of underlying dynamical system and measuring its parameters (dimension, Lyapunov exponents etc.) from these data is hardly possible and more adequate is application of statistical techniques.
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Introductione seen within the particular environment, which justifies the restriction to physiological data. Nevertheless, many problems occurring in the treatment of physiological data will be encountered also in other fields, such as the problem of nonstationarity.
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Chaotic Measures and Real-World Systems relatively small scales are used. The distinction can be reestablished by using larger scales. Using larger scales, however, the estimated Lyapunov exponent is determined by macroscopic statistical properties of the series and provides the same information as the autocorrelation function and/or coarse-grained mutual information.
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