Title :
Models of cyclic oscillation using VLSI-based neural elements
Author_Institution :
Dept. of Electr. Eng., Maine Univ., Orono, ME, USA
Abstract :
As a prelude to the VLSI implementation of a biologically-based locomotory network, the phenomenon of recurrent cyclic inhibition was recreated in VLSI-based artificial neurons for parametric analysis of its oscillatory range and stability. The IC-based artificial neurons used in this study are behaviorally comprehensive and highly configurable, allowing for a variety of transient and steady characteristics to be precisely and continuously adjustable. Circuit tests indicate that recurrent cyclic inhibitory prototypes do not require synaptic dynamics, and show remarkable stability, even when the self-excitatory frequency of each component neuron varies over two orders of magnitude
Keywords :
VLSI; IC-based artificial neurons; VLSI implementation; VLSI-based neural elements; behaviorally comprehensive neurons; biologically-based locomotory network; circuit tests; cyclic oscillation models; highly configurable neurons; oscillatory range; parametric analysis; self-excitatory frequency; stability; steady characteristics; synaptic dynamics; transient characteristics; Automatic testing; Biological system modeling; Biomembranes; Circuit stability; Circuit testing; Frequency; Neurons; Oscillators; Prototypes; Stability analysis;
Conference_Titel :
Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-2050-6
DOI :
10.1109/IEMBS.1994.415349