A recurrent fuzzy neuron for on line modelling of nonlinear systems

Abstract:

This paper presents a recurrent fuzzy neuron (RFN) which facilitates nonlinear mapping from an input space to an output space. The synaptic junctions are characterized by a set of IF-THEN rules and recurrent characteristics provide dynamic properties to the neuron, allowing its application to on line modelling for a variety of nonlinear systems. The effectiveness of this neuron to synthesize complex nonlinear models, is illustrated by simulation results related to on line pbkp_rediction of chaotic behavior and modelling of time varying nonlinear systems.

Año de publicación:

2002

Keywords:

• Neural dynamics
• Nonlinear models
• fuzzy systems
• Dynamic modelling

Fuente:

scopus