Publication Type:

Conference Paper

Source:

2011 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2011, Trivandrum, Kerala, p.129-133 (2011)

ISBN:

9781424494774

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-81355163865&partnerID=40&md5=dece2e0f70333be9e703a1f9899171fc

Keywords:

Blind source separation, Computational complexity, Estimation techniques, Filter banks, Filter-bank coefficients, Instruments, Musical instruments, Musical notes, NLMS algorithm, Scaling functions, Separation, Unmixing, Wavelet function, Wavelet transforms, Window functions

Abstract:

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. © 2011 IEEE.

Notes:

cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@2e5ed2cc ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@536166dc Through org.apache.xalan.xsltc.dom.DOMAdapter@1fa82048; Conference Code:87395

Cite this Research Publication

M. Sa Sinith, Nair, M. Nb, Nair, N. Pb, and Parvathy, Sb, “Blind Source Separation of musical instrument signals by identification of wavelets and filter bank coefficients”, in 2011 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2011, Trivandrum, Kerala, 2011, pp. 129-133.