Efficient Multiplierless FPGA Architecture for Brain-Inspired
Efficient Multiplierless FPGA Architecture for Brain-Inspired Rulkov Neuron Mapping
Abstract:
This brief presents a high-efficiency, multiplierless Field-Programmable Gate Array (FPGA) realization of the Rulkov neuron map using a hybrid approximation framework. The proposed approach integrates High-Frequency Point Detec-tion (HFPD) for accurate spiking approximation and Exponential Binary Power (EBP) computed via Coordinate Rotation Digital Computer (CORDIC) for efficient bursting dynamics, fully elimi-nating multipliers and dividers. Implemented on a Xilinx Virtex-4 FPGA, the design achieves a synthesis frequency of 276.9 MHz, reduces hardware utilization by 30%, and improves speed by 1.27× compared to the baseline. An average Root Mean Squared Error (RMSE) of 0.54 and successful two-coupled and ten-multiplexed implementations confirm the accuracy, scalability, Received 13 November 2025; revised 15 December 2025; accepted 20 December 2025. Date of publication 26 December 2025; date of current version 2 March 2026. This work was supported in part by Natural Science Foundation of Zhejiang Province (LQ24F030013); in part by Wenzhou Major Scientific and Technological Innovation Project (Grant No. ZY2024025) and Wenzhou Key Laboratory of Cardiopulmonary and Brain Resuscitation and Rehabilitation Application Transformation; in part by Jiaxing City Science and Technology Plan Project (No. 2024AY40027); in part by Key Laboratory Open Fund of Fujian Province(KYZ286825007). The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP2/415/46. This brief was recommended by Associate Editor F. G. Moraes. (Corresponding authors: Abdulilah Mohammad Mayet; Xiaotian Pan; Guodao Zhang; Xinjun Miao.) Huan Chen is with the Department of Emergency, Wenzhou Central Hospital, Wenzhou Medical University, Wenzhou 325000, China (e-mail: chenhuan1226@wmu.edu.cn).
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Efficient Multiplierless FPGA Architecture for Brain-Inspired Rulkov Neuron Mapping
