Title :
Bifurcation analysis of a reconfigurable hybrid spiking neuron and its novel online learning algorithm
Author :
Hashimoto, Sho ; Torikai, Hiroyuki
Author_Institution :
Grad. Sch. of Eng. Sci., Osaka Univ., Suita, Japan
Abstract :
A hybrid spiking neuron is a wired system of shift registers and behaves like a neuron model. The neuron exhibits various bifurcation phenomena and response characteristics for a stimulation spike-train input. In this paper we formulate some typical bifurcation mechanisms and clarify these mechanisms by using discrete/continuous hybrid maps. Based on the analysis results, we can clarify mechanisms of various responses of the neuron. In addition, we propose a novel online learning algorithm of the neuron and show that the neuron can reconstruct or approximate response characteristics of another neuron with unknown parameter values.
Keywords :
bifurcation; learning (artificial intelligence); neural nets; shift registers; bifurcation analysis; bifurcation mechanisms; continuous hybrid maps; discrete hybrid maps; neuron model; online learning algorithm; reconfigurable hybrid spiking neuron; shift registers; stimulation spike-train input; Algorithm design and analysis; Arithmetic; Bifurcation; Current measurement; Field programmable analog arrays; Field programmable gate arrays; Neural networks; Neurons; Shift registers; Wiring;
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2009.5178757