estradiol
发表于 2025-3-21 19:53:33
书目名称Nonlinear Analysis of Physiological Data影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0667330<br><br> <br><br>书目名称Nonlinear Analysis of Physiological Data读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0667330<br><br> <br><br>
出血
发表于 2025-3-21 22:16:02
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
CLIFF
发表于 2025-3-22 01:08:32
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.
滴注
发表于 2025-3-22 08:25:14
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.
genuine
发表于 2025-3-22 09:24:25
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.
Gudgeon
发表于 2025-3-22 13:29:16
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VALID
发表于 2025-3-22 17:56:16
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.
Harness
发表于 2025-3-22 22:31:10
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.
伸展
发表于 2025-3-23 02:08:54
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peptic-ulcer
发表于 2025-3-23 07:03:56
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