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A FPGA Implementation of the CAR-FAC Cochlear Model.

Ying Xu1, Chetan S Thakur1, Ram K Singh1

  • 1MARCS Institute, Western Sydney University, Sydney, NSW, Australia.

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|April 26, 2018
PubMed
Summary

This study details a digital cochlear model (CAR-FAC) simulating hearing functions. The implemented system is stable, scalable, and ideal for advanced machine hearing applications.

Keywords:
FPGAsautomatic gain controlbasilar membraneelectronic cochleainner hair cellmedial olivocochlear efferentneuromorphic engineeringouter hair cell

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Area of Science:

  • Auditory Neuroscience
  • Digital Signal Processing
  • Biomedical Engineering

Background:

  • The human cochlea processes sound via the basilar membrane (BM) and hair cells.
  • Modeling cochlear functions is crucial for understanding hearing and developing hearing prostheses.
  • Existing models often lack the dynamic feedback mechanisms present in biological systems.

Purpose of the Study:

  • To present a fully digital implementation of the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model.
  • To demonstrate the feasibility of implementing complex auditory models on Field Programmable Gate Arrays (FPGAs).
  • To provide a stable, scalable, and reconfigurable platform for advanced machine hearing research.

Main Methods:

  • Digital implementation of the CAR-FAC model, comprising basilar membrane (BM) simulation (CAR) and hair cell/efferent system modeling (FAC).
  • Feedback mechanism where FAC adjusts CAR resonator poles and zeros.
  • Implementation on an Altera Cyclone V FPGA using time-multiplexing and pipeline parallelizing techniques at a 44.1 kHz sampling rate.

Main Results:

  • Successful digital implementation of a 70-section CAR-FAC system on an FPGA.
  • Achieved 18% ALM utilization on the FPGA.
  • Demonstrated system stability, scalability, and ease of use through measurement results.

Conclusions:

  • The digital CAR-FAC system offers a robust and efficient simulation of cochlear processing.
  • This FPGA-based model serves as an excellent input stage for complex machine hearing tasks.
  • The reconfigurable nature of the digital system facilitates further research and development in artificial hearing.