A survey of filter bank algorithms for biomedical applications

N. Subbulakshmi, R. Manimegalai
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引用次数: 11

Abstract

The Digital signal processing algorithms are promising techniques, which are used to alleviate the filter bank designs in various applications. Filter bank is an enabling technique for numerous capabilities such as speech coding, Noise reduction, Sub band coding and auditory compensation. The design procedure mainly concentrates on the core part of the system which is the type of the filter. However, it imposes several solutions to many problems high computation complexity, area and power consumption are most critical concern. In digital hearing aid application, the filter bank improves the sound ability for hearing-impaired people. The scope of this work is to give an overview of the filter bank algorithms under various traits and the challenges that they face, along with the current state-of-the-art. To enhance the feasibility of the design by applying the characteristics of the filter banks for suitable applications. This paper covers wide range of issues in the design of filter bank. The contribution of this paper is threefold. First, we show the functional role of filter bank. Second, the classifications of filter bank algorithms for the hearing instruments. Third, merits, demerits and further design challenges of the filter banks are discussed.
生物医学应用滤波器组算法综述
数字信号处理算法是一种很有前途的技术,可用于减轻各种应用中滤波器组的设计。滤波器组是一种支持多种功能的技术,如语音编码、降噪、子带编码和听觉补偿。设计过程主要集中在系统的核心部分,即滤波器的类型。然而,它对许多问题提出了不同的解决方案,高计算复杂度、面积和功耗是最关键的问题。在数字助听器应用中,滤波器组提高了听障人士的声音能力。这项工作的范围是概述各种特征下的滤波器组算法及其面临的挑战,以及当前的最新技术。通过将滤波器组的特性应用于合适的应用场合,提高设计的可行性。本文讨论了滤波器组设计中的广泛问题。本文的贡献有三个方面。首先,我们展示了滤波器组的功能作用。第二,助听器滤波器组算法的分类。第三,讨论了滤波器组的优点、缺点和进一步的设计挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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