Possibilistic Entropy: A New Method for Nonlinear Dynamical Analysis of Biosignals
Conference paper
Abstract
The theory of nonlinear dynamical systems has opened doors to discovering potential patterns hidden in complex time-series data. An attrative approach to nonlinear time-series analysis is the measure of predictability which characterizes the data in terms of entropy. A new entropy measure is presented in this paper as a new nonlinear dynamical method, which is based on the theory of possibility and the kriging computation. The proposed model has the potential for studying complex biosignals.
Keywords
Major Adverse Cardiac Event Ordinary Krig Anion Exchange Resin Entropy Measure Nonlinear Dynamical Analysis
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