A Robust Algorithm for Optimisation and Customisation of Fractal Dimensions of Time Series Modified by Nonlinearly Scaling Their Time Derivatives: Mathematical Theory and Practical Applications
Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is...
Main Author: | Franz Konstantin Fuss |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2013-01-01
|
Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2013/178476 |
Similar Items
-
Robust Forecasting For Nonlinear Time Series
by: Liu, Yung-shan, et al.
Published: (1993) -
Customised optimisation for the planning and scheduling of utility systems
by: Strouvalis, A. M.
Published: (2000) -
Fractal dimension analysis of the magnetic time series associated with the volcanic activity of Popocatépetl
by: E. L. Flores-Marquez, et al.
Published: (2012-12-01) -
Customisable and reconfigurable platform for optimising floating point computations
by: Hok Ho, Chun
Published: (2010) -
Modifying an architecture for interface customisation support
by: Nilsson, Martin Persson and Johan
Published: (2002)