FPGA实现计算机的CAR模型
FPGA Implementation of the CAR Model of the Cochlea
摘要：
人类听觉系统的前端，耳蜗，将来自外界的声音信号转换成沿着听觉通路传输的神经脉冲，以进行进一步处理。耳蜗以非线性的主动方式感知和分离声音，表现出显着的灵敏度和频率辨别力。尽管已经提出并实现了耳蜗的几种电子模型，但是这些模型都不能再现耳蜗的所有特性，包括大动态范围、大增益和在低声级下的尖锐调谐以及在强声级下的低增益和宽调谐。在这里，我们在FPGA上实现了耳蜗的级联非对称谐振器（CAR）模型。CAR表示具有快速作用压缩的非对称谐振器级联（CAR-FAC）耳蜗模型中的基底膜滤波器。CAR-FAC是基于听觉滤波的极零滤波器级联模型的听觉神经形态模型。它使用了非常适合FPGA实现的传统数字滤波器级的简单非线性扩展，因此我们能够在Virtex-6 FPGA上实现多达1224个耳蜗部分，以实时的处理声音数据。这里描述的电子耳蜗的FPGA实现可以用作各种机器听力应用的前端声音分析器。
英文摘要：
The front end of the human auditory system, the cochlea, converts sound signals from the outside world into neural impulses transmitted along the auditory pathway for further processing. The cochlea senses and separates sound in a nonlinear active fashion, exhibiting remarkable sensitivity and frequency discrimination. Although several electronic models of the cochlea have been proposed and implemented, none of these are able to reproduce all the characteristics of the cochlea, including large dynamic range, large gain and sharp tuning at low sound levels, and low gain and broad tuning at intense sound levels. Here, we implement the Cascade of Asymmetric Resonators (CAR) model of the cochlea on an FPGA. CAR represents the basilar membrane filter in the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model. CAR-FAC is a neuromorphic model of hearing based on a pole-zero filter cascade model of auditory filtering. It uses simple nonlinear extensions of conventional digital filter stages that are well suited to FPGA implementations, so that we are able to implement up to 1224 cochlear sections on Virtex-6 FPGA to process sound data in real time. The FPGA implementation of the electronic cochlea described here may be used as a front-end sound analyser for various machine-hearing applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
