The human brain is the most complex information processing system that exists in nature. Its information processing functionality exists at multiple levels of interactions which can be influenced by electrical, chemical and physical components governed by thresholds and saturation phenomena [
]. When these thresholds are exceeded, saturation is reached, giving rise to nonlinear behaviour [
- Abasolo D.
- Hornero R.
- Espino P.
- Álvarez D.
- Poza J.
Entropy analysis of the EEG background activity in Alzheimer's disease patients.
Physiol. Meas. 2006; 27: 241-253
]. The human brain like most dynamic systems in nature typically exhibit chaotic and complex behaviours with nonlinear dynamic properties [
- Sokunbi M.O.
- Gradin V.B.
- Waiter G.D.
- Cameron G.G.
- Ahearn T.S.
- Murray A.D.
- Steele D.J.
- Staff R.T.
Nonlinear complexity analysis of brain fMRI signals in schizophrenia.
PLoS One. 2014; 9: e95146
]. This chaotic and complex behaviour has prompted the need for methods that can be used to characterise the human brain in a nonlinear manner.
- Bertolaccini M.
- Bussolati C.
- Padovini G.
A nonlinear filtering technique for the identification of biological signals.
IEEE Trans. Biomed. Eng. 1978; 25: 159-165
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Published online: June 22, 2016
Accepted: June 16, 2016
Received in revised form: June 15, 2016
Received: May 18, 2016
© 2016 Elsevier B.V. All rights reserved.