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FPGA-Efficient Digital Implementation of a Multiplierless Cochlea-Neuron Interaction Model for Industrial-Scale Neural Systems
Author(s) -
Songjie Xiang,
Ru Chen,
Die Yu,
Hailing Liu,
Mohammad Sh. Daoud,
Guodao Zhang,
Yanling Chu,
Abdulilah Mohammad Mayet,
Yideng Huang
Publication year - 2025
Publication title -
ieee open journal of the industrial electronics society
Language(s) - English
Resource type - Magazines
eISSN - 2644-1284
DOI - 10.1109/ojies.2025.3592720
Subject(s) - components, circuits, devices and systems , power, energy and industry applications
This paper presents a novel digital design methodology for modeling cochlea-neuron interactions, tailored for applications within the scope of industrial electronics, such as real-time biosensing, smart health interfaces, and resource-aware neural signal processing. The proposed model employs a simplified two-dimensional cochlear structure based on the Hopf oscillator, optimized using Linear Shift-ADD-Based (LS-A-B) functions and Look-Up Table-Based Sampling (LUT-BS) to eliminate complex multipliers and achieve hardware-friendly, high-speed performance. This hybrid multiplierless architecture aligns with the journal's focus on efficient digital realization of intelligent systems and FPGA-based electronic designs. The resulting Cochlea-Neuron Interaction Circuit (C-NIC), when implemented on a Xilinx Virtex-II FPGA, demonstrates 1.33× speed-up and supports up to 87 parallel cochlear modules, while maintaining high signal fidelity and neural activation accuracy. Simulation and hardware validation confirm that the proposed system provides a scalable, low-resource solution suitable for emerging industrial biosensing systems, smart auditory devices, and embedded neural interfaces. The methodology contributes to advancing the real-time digital implementation of biologically-inspired systems in industrial and biomedical electronics.

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