CIOP 05384
CENTRO DE INVESTIGACIONES OPTICAS
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Using the permutation entropy to detect nonlinearity in short and noisy time series data
Autor/es:
LUCIANO ZUNINO; CHRISTOPHER KULP
Lugar:
Silver Spring, MD, USA
Reunión:
Conferencia; Dynamics Days 2017; 2017
Institución organizadora:
Institute for Research in Electronics and Applied Physics at the University of Maryland
Resumen:
In this poster we present a study demonstrating the effectiveness of the permutation entropy in detecting nonlinearity in time series data. The study is performed by comparing the permutation entropy of a model or experimental time series to the permutation entropy of an ensemble of surrogates. It is found that the permutation entropy is a robust discriminator of nonlinearity in short and noisy time series data.
