Stability of Amygdala Learning System using Cell-to-Cell Mapping Algorithm

D. Shahmirzadi and R. Langari (USA)


Amygdala Learning, Stability, Cell-To-Cell Mapping


In this paper, we study the stability of a biologically motivated system, termed BEL-Brain Emotional Learning, using the Cell-To-Cell mapping method. The BEL system is a learning algorithm, which is mainly applied in control problems, and hence, its stability properties are of most important to investigate. Because of the nonlinearity and complicacy of the governing equations, investigating the stability of the system using analytical methods, e.g. Lyapunov theory, turns out to be very cumbersome. On the other hand, the Cell-To-Cell mapping algorithm is a numerical method to examine the behavior of the systems where the nonlinearities can be easily incorporated. The Cell-To-Cell mapping method is used to investigate the stability of the BEL system. The results enabled us to infer the behavior of the system with respect to changing different parameters of the system and gave a general idea of how to choose the control parameters to ensure stability.

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