학술논문

Space-and-Cost-Efficient Neural Control /Sensory Element Using an Analog FPGA
Document Type
Conference
Source
2019 International Conference on System Science and Engineering (ICSSE) System Science and Engineering (ICSSE), 2019 International Conference on. :71-74 Jul, 2019
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Neurons
Integrated circuit modeling
Artificial neural networks
Biological neural networks
Field programmable gate arrays
Software
Clocks
Anadigm dpASP
Cypress PSoC
multiplying DA C
switched-capacitor techniques
exhaustive search
Language
ISSN
2325-0925
Abstract
As neural networks are applied to control and sensory, software neuron models cannot sometimes fulfill speed requirement as well as simple add-and-sigmoid is not enough for functionality. This paper proposes a small and inexpensive hardware neuron based on FitzHugh-Nagumo model. By making full use of chip property and maximum circuit packing through placement search, it surpasses the previous implementation by factors of 4 for space and 15 for cost.