Quantized-state approximation of nonlinear dynamical systems for hardware-efficient implementation
Year: 2025
Type: article
Abstract: Nonlinear dynamical systems such as biological systems require substantial resources for digital circuit implementation due to their nonlinearity. This study approximates these systems by converting to the quantized-state system (QSS) solved using the forward Euler method and efficiently implements them on a field-programmable gate array (FPGA). Focusing on coupled nonlinear oscillators that mimic neural circuits, we evaluate the benefits and limitations of the QSS in terms of hardware resource usage and accuracy compared to the original system solved using the forward Euler method. The results provide valuable insights for the miniaturization and energy efficiency of neuromorphic hardware.
Source: IEICE Electronics Express
Author: Kentaro Takeda
Institution: Kagawa University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410736331