DocumentCode :
315179
Title :
Equivalent dynamics in different neural oscillator models
Author :
Berdux, Jörg ; Malaka, Rainer
Author_Institution :
Inst. fur Logik, Komplexitat und Deduktionssyst., Karlsruhe Univ., Germany
Volume :
2
fYear :
1997
fDate :
9-12 Jun 1997
Firstpage :
675
Abstract :
This paper introduces a method of model transformation for neural oscillators defined by a set of ordinary differential equations and a nonlinearity and gives an example for two popular neural oscillator models. The method finds the parameters of one oscillator model such that its dynamics are equivalent to that of another oscillator model. Although this equivalence is obtained using the assumption of harmonic oscillations, it can be shown in simulations that these transformed neural oscillators not only behave equivalently in the state of harmonic balance, but also mainly equivalent in stationary and chaotic activation states. Moreover, even networks consisting of those oscillators show equivalent dynamics under very different dynamic regimes
Keywords :
chaos; dynamics; harmonic oscillators; oscillations; recurrent neural nets; chaotic activation states; harmonic balance; harmonic oscillations; model transformation; neural oscillator models; nonlinearity; ordinary differential equations; stationary activation states; Chaos; Computational modeling; Computer simulation; Differential equations; Information processing; Laplace equations; Linearity; Mathematical model; Oscillators; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
Type :
conf
DOI :
10.1109/ICNN.1997.616102
Filename :
616102
Link To Document :
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