arXiv subjects

Joachim Peinke

Publications and source records attributed to Joachim Peinke.

62 records · Page 4Linked to original sources

arXiv2010

Effects of Sudden Changes in Inflow Conditions on the Angle of Attack on HAWT Blades

In this paper changes in wind speed and wind direction from a measured wind field are being analyzed at high frequencies. This is used to estimate changes in the angle of attack (AOA) on a blade segment over short time periods for different estimated turbine concepts. Here a statistical approach is chosen to grasp the characteristics of the probability distributions to give an over all view of the magnitude and rate of the changes. The main interest is the generation of basic distributions for the calculation of dynamic stall effects and stall flutter due to wind fluctuations.

stat.AP↗

arXiv2007

Markov properties in presence of measurement noise

Recently, several powerful tools for the reconstruction of stochastic differential equations from measured data sets have been proposed [e.g. Siegert et al., Physics Letters A 243, 275 (1998); Hurn et al., Journal of Time Series Analysis 24, 45 (2003)]. Efficient application of the methods, however, generally requires Markov properties to be fulfilled. This constraint typically seems to be violated on small scales, which frequently is attributed to physical effects. On the other hand, measurement noise such as uncorrelated measurement and discretization errors has large impacts on the statistics of measurements on small scales. We demonstrate, that the presence of measurement noise, likewise, spoils Markov properties of an underlying Markov processes. This fact is promising for the further development of techniques for the reconstruction of stochastic processes from measured data, since limitations at small scales might stem from artificial noise sources rather than from intrinsic properties of the dynamics of the underlying process. Measurement noise, however, can be controlled much better than the intrinsic dynamics of the underlying process.

physics.data-an↗

arXiv2006

Medium and Small Scale Analysis of Financial Data

A stochastic analysis of financial data is presented. In particular we investigate how the statistics of log returns change with different time delays $τ$. The scale dependent behaviour of financial data can be divided into two regions. The first time-range, the small-timescale region (in the range of seconds) seems to be characterized by universal features. The second time-range, the medium-timescale range from several minutes upwards and can be characterized by a cascade process, which is given by a stochastic Markov process in the scale $τ$. A corresponding Fokker-Planck equation can be extracted from given data and provides a non equilibrium thermodynamical description of the complexity of financial data.

physics.data-an↗

arXiv2006

On the proper reconstruction of complex dynamical systems spoilt by strong measurement noise

This article reports on a new approach to properly analyze time series of dynamical systems which are spoilt by the simultaneous presence of dynamical noise and measurement noise. It is shown that even strong external measurement noise as well as dynamical noise which is an intrinsic part of the dynamical process can be quantified correctly, solely on the basis of measured times series and proper data analysis. Finally real world data sets are presented pointing out the relevance of the new approach.

nlin.CD↗

arXiv2006

New Computational Approaches to Analysis of Interbeat Intervals in Human Subjects

We investigate the Markov nature, Cascade of information from large time scale to small scale and extended self similarity properties of the beat to beat fluctuations of healthy subjects as well as those with congestive heart failure. To check the Markov nature, we use a novel inverse method that utilizes a set of data to construct a simple equation that governs the stochastic process for which the data have been measured, hence enabling us to reconstruct the stochastic process. The inverse method provides a novel technique for distinguishing the two classes of subjects in terms of a drift and a diffusion coefficients which behave completely differently for the two classes of subjects.To investigate the cascade of information from large to small time scales we also analyze the statistical properties of interbeat intervals cascade by considering the joint probability distribution for two interbeat increments. As a result, the joint probability distributions of the increments in the interbeat intervals obey a Fokker-Planck equation. Finally we analyze the extended self-similarity (ESS) in the beat-to-beat fluctuations in the heart rates of healthy and congestive heart failure subjects.The proposed methods provide the novel techniques for distinguishing the two classes of subjects in terms of the drift and diffusion coefficients, intermittency exponents which behave differently for two classes of the subjects, namely, healthy subjects and those with congestive heart failure.

q-bio.QM↗

arXiv2005

Small scale behavior of financial data

A new approach is presented to describe the change in the statistics of the log return distribution of financial data as a function of the timescale. To this purpose a measure is introduced, which quantifies the distance of a considered distribution to a reference distribution. The existence of a small timescale regime is demonstrated, which exhibits different properties compared to the normal timescale regime. This regime seems to be universal for individual stocks. It is shown that the existence of this small timescale regime is not dependent on the special choice of the distance measure or the reference distribution. These findings have important implications for risk analysis, in particular for the probability of extreme events.

physics.data-an↗

arXiv2004

Increment definitions for scale dependent analysis of stochastic data

It is common for scale-dependent analysis of stochastic data to use the increment $Δ(t,r) = ξ(t+r) - ξ(t)$ of a data set $ξ(t)$ as a stochastic measure, where $r$ denotes the scale. For joint statistics of $Δ(t,r)$ and $Δ(t,r')$ the question how to nest the increments on different scales $r,r'$ is investigated. Here we show that in some cases spurious correlations between scales can be introduced by the common left-justified definition. The consequences for a Markov process are discussed. These spurious correlations can be avoided by an appropriate nesting of increments. We demonstrate this effect for different data sets and show how it can be detected and quantified. The problem allows to propose a unique method to distinguish between experimental data generated by a noiselike or a Langevin-like random-walk process, respectively.

physics.data-an↗

arXiv1999

How to quantify deterministic and random influences on the statistics of the foreign exchange market

It is shown that prize changes of the US dollar - German Mark exchange rates upon different delay times can be regarded as a stochastic Marcovian process. Furthermore we show that from the empirical data the Kramers-Moyal coefficients can be estimated. Finally, we present an explicite Fokker-Planck equation which models very precisely the empirical probabilitiy distributions.

physics.data-an↗