High-Selectivity Filter Banks for Spectral Analysis of Music Signals
High-Selectivity Filter Banks for Spectral Analysis of Music Signals
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DOI：
10.1155/2007/94704
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发表时间：
2007
影响因子：
1.9
通讯作者：
F. Diniz;I. Kothe;S. L. Netto;L. Biscainho
中科院分区：
文献类型：
--
作者：
F. Diniz;I. Kothe;S. L. Netto;L. Biscainho
本文在一个统一的框架下，探讨了音乐信号频谱分析的几种算法。这些算法包括快速傅立叶变换（FFT）、快速滤波器组（FFB）、常数变换（CT）和有界变换（BT），这些算法在之前的相关文献中已经有所介绍。结合上述算法的优点，提出了恒快滤波器组（CFFB）和有界快滤波器组（BFFB）两种新方法。所提供的分析表明，所提出的BFFB在减少FFT的计算量，FFB的每个输出通道的高选择性以及与CT和BT方法相关的频率通道的有效分配之间取得了很好的折衷。举例说明了这些方法在音乐信号的频谱分析中的性能。
This paper approaches, under a unified framework, several algorithms for the spectral analysis of musical signals. Such algorithms include the fast Fourier transform (FFT), the fast filter bank (FFB), the constant- transform (CT), and the bounded- transform (BT), previously known from the associated literature. Two new methods are then introduced, namely, the constant- fast filter bank (CFFB) and the bounded- fast filter bank (BFFB), combining the positive characteristics of the previously mentioned algorithms. The provided analyses indicate that the proposed BFFB achieves an excellent compromise between the reduced computational effort of the FFT, the high selectivity of each output channel of the FFB, and the efficient distribution of frequency channels associated to the CT and BT methods. Examples are included to illustrate the performances of these methods in the spectral analysis of music signals.