Online Learning of Cricket Auditory Network in FPGA-Based SNN
Seiya Homma, Haruto Ota, Ryuji Nagazawa, Kien Nguyen, Hiroo Sekiya
2025 International Symposium on Nonlinear Theory and Its Applications (NOLTA), Oct., 2025. [pdf document]

<Abstract>

This paper presents a system that mimics the cricket auditory feature detection circuit, reproducing its functionality using an Field-Programmable Gate Array (FPGA). The system utilizes a Spiking Neural Network (SNN) based on the Izhikevich model, and its neural parameters are optimized via external control. Consequently, the system successfully reproduces the cricket’s selective response, demonstrating the feasibility of using FPGAs to mimic biological neural networks.