利用小波技术改善人工耳蜗的信噪比、滤波和频谱均衡

C. Behrenbruch, B. Lithgow
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引用次数: 5

摘要

本文简要介绍了基于小波技术的人工耳蜗语音处理器的工程要求。人工耳蜗的信号处理通常包括滤波和噪声去除、频谱估计(对听力受损个体的频率响应)和期望频率的均衡。这些不同的信号处理功能通常使用单独的硬件和微处理器阶段来实现。相反,小波分析固有地支持特征提取、环境噪声去除和通过使用选定的频率局部函数进行频谱估计。适当的基选择可以考虑噪声、频谱和均衡(缩放)。因此,可以将各种信号处理要求集成到一个基于dsp(数字信号处理器)的解决方案中。
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SNR improvement, filtering and spectral equalisation in cochlear implants using wavelet techniques
This paper contains a brief outline of the engineering requirements for a cochlear implant speech processor based on wavelet techniques. Signal processing in cochlear implants typically involves filtering and noise removal, spectral estimation (to the frequency response of the hearing-impaired individual) and equalisation across desired frequencies. These various signal processing functions are typically implemented using separate hardware and microprocessor stages. In contrast, wavelet analysis inherently supports feature extraction, ambient noise removal and spectral estimation through the use of selected frequency-localised functions. Appropriate basis selection can incorporate noise, spectrum and equalisation (scaling) considerations. Thus it is possible to integrate the various signal processing requirements into a single DSP-based (digital signal processor) solution.
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