A Novel Hardware-Oriented Recurrent Network of Asynchronous CA Neurons for a Neural Integrator

• Published in: IEEE transactions on circuits and systems. II, Express briefs Vol. 68; no. 8; pp. 2972 - 2976
• Main Authors: Takeda, Kentaro, Torikai, Hiroyuki
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-08-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biological system modeling; Cellular automata; Clocks; Computational modeling; Differential equations; Field programmable gate arrays; Hardware; Hysteresis; Integrated circuit modeling; Mathematical model; Neural integrator; Neurons; Ordinary differential equations; Power consumption; spiking neural network
• ISSN: 1549-7747; 1558-3791
• DOI: 10.1109/TCSII.2021.3063932

In this brief, a recurrent network was derived for a neural integrator (NI) described by an ordinary differential equation (ODE) that can be solved with fewer computational resources. Subsequently, based on the reduced ODE model, a hardware-oriented recurrent network model was proposed for a NI consisting of asynchronous cellular automaton (CA) neurons. The proposed model, reduced ODE model, and the previously proposed NI model were implemented on a field-programmable gate array. Analysis results suggest that the proposed model consumes fewer hardware resources and lower power than those of the reduced ODE model and the previously proposed NI model.