ArticleFrontiers in neuroscience2018
A FPGA Implementation of the CAR-FAC Cochlear Model.
Article in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Dynamic sensor adaptation based on efferent feedback for adaptive bio-inspired sound source localization.Frontiers in neuroscience · 2026Article
- Cochleogram-Based Speech Emotion Recognition with the Cascade of Asymmetric Resonators with Fast-Acting Compression Using Time-Distributed Convolutional Long Short-Term Memory and Support Vector Machines.Biomimetics (Basel, Switzerland) · 2025Article
- Event-driven spectrotemporal feature extraction and classification using a silicon cochlea model.Frontiers in neuroscience · 2023Article
- A bioinspired configurable cochlea based on memristors.Frontiers in neuroscience · 2022Article
- Periodicity Pitch Perception.Frontiers in neuroscience · 2020Article
- Modeling Pitch Perception With an Active Auditory Model Extended by Octopus Cells.Frontiers in neuroscience · 2018Article
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Authors and funding
6 authors.
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Abstract
This paper presents a digital implementation of the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model. The CAR part simulates the basilar membrane's (BM) response to sound. The FAC part models the outer hair cell (OHC), the inner hair cell (IHC), and the medial olivocochlear efferent system functions. The FAC feeds back to the CAR by moving the poles and zeros of the CAR resonators automatically. We have implemented a 70-section, 44.1 kHz sampling rate CAR-FAC system on an Altera Cyclone V Field Programmable Gate Array (FPGA) with 18% ALM utilization by using time-multiplexing and pipeline parallelizing techniques and present measurement results here. The fully digital reconfigurable CAR-FAC system is stable, scalable, easy to use, and provides an excellent input stage to more complex machine hearing tasks such as sound localization, sound segregation, speech recognition, and so on.
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