Title :
Simple noise reduction in the adaptive synchronization of coupled neurons by Robust Fixed Point Transformation
Author :
Várkonyi, Teréz A. ; Tar, József K. ; Bitó, János F. ; Rudas, Imre J.
Author_Institution :
John von Neumann Fac. of Inf., Obuda Univ., Budapest, Hungary
Abstract :
To avoid the general mathematical difficulties of the application of Lyapunov´s “direct” method in adaptive control in the present paper an alternative approach, the use of “Robust Fixed Point Transformation (RFPT)” is applied for the adaptive synchronization of two coupled, asymmetric, chaotically behaving, approximately known Fitz - Hugh - Nagumo (FHN) neurons. Since the RFPT scheme is based on the use of the “Expected - Realized Response Scheme” the noise in the observed quantities may influence the efficiency of the controller. For this purpose the use of a very simple, easily realizable technique is proposed that applies polynomial filtering coefficients in the time domain. Its efficiency is investigated and substantiated via extended simulation investigations.
Keywords :
adaptive control; chaos; filtering theory; neurocontrollers; nonlinear control systems; synchronisation; Fitz-Hugh-Nagumo neuron; adaptive controller; chaotic motion; expected-realized response scheme; neuron adaptive synchronization; noise reduction; polynomial filtering coefficient; robust fixed point transformation; Adaptation models; Adaptive systems; Chaos; Neurons; Noise; PD control; Synchronization;
Conference_Titel :
Intelligent Engineering Systems (INES), 2011 15th IEEE International Conference on
Conference_Location :
Poprad
Print_ISBN :
978-1-4244-8954-1
DOI :
10.1109/INES.2011.5954762