基于小波识别和滤波器组系数的乐器信号盲源分离

M. Sinith, M. N. Nair, Niveditha P. Nair, S. Parvathy
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引用次数: 3

摘要

本文提出了一种新的盲源分离(BSS)方法,将乐器中识别出的小波作为退化解混估计技术(DUET)算法的窗函数。给出了乐器、小提琴和长笛中存在的小波的尺度函数和小波函数。NLMS算法用于识别在乐器音符中发现重复的类小波元素的滤波器组系数。采用NLMS算法迭代求出标准小波的尺度函数。开发了适用于不同乐器的小波。将得到的小波应用到DUET算法中,实现对乐器信号混合源的BSS。
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Blind Source Separation of musical instrument signals by identification of wavelets and filter bank coefficients
This paper, presents a new approach in Blind Source Separation (BSS) using identified wavelets in musical instruments as window function in the Degenerate Unmixing Estimation Technique (DUET) algorithm. the scaling function and the wavelet functions of the wavelets present in musical instruments, violin and flute is presented. NLMS algorithm is used to identify the filter bank coefficients of wavelet-like elements, found repeating in musical notes of the instruments. Scaling functions of the standard wavelets are also found out by an iterative manner using NLMS algorithm. wavelets for different musical instruments are developed. The obtained wavelets are utilized in the DUET algorithm to achieve the goal of BSS to the mixed source of music instruments signals.
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