Blind audio source separation based on a new system model and the Savitzky-Golay filter

Author:

Xu Pengfei1,Jia Yinjie12,Jiang Mingxin2

Affiliation:

1. Hohai University , College of Computer and Information , Nanjing , China

2. Huaiyin Institute of Technology, Faculty of Electronic Information Engineering , Huaian , China

Abstract

Abstract Blind source separation (BSS) is a research hotspot in the field of signal processing. This scheme is widely applied to separate a group of source signals from a given set of observations or mixed signals. In the present study, the Savitzky-Golay filter is applied to smooth the mixed signals, adopt a simplified cost function based on the signal to noise ratio (SNR) and obtain the demixing matrix accordingly. To this end, the generalized eigenvalue problem is solved without conventional iterative methods. It is founded that the proposed algorithm has a simple structure and can be easily implemented in diverse problems. The obtained results demonstrate the good performance of the proposed model for separating audio signals in cases with high signal to noise ratios.

Publisher

Walter de Gruyter GmbH

Reference16 articles.

1. [1] J. Herault, C. Jutten, and B. Ans, “Détection de grandeurs primitives dans un message composite par une architecture de calcul neuromimetique en apprentissage non supervise”, Proceedings of the 10 th Symposium on Signal and Image Processing, Nice, France, pp. 1017-1022 (1985).

2. [2] P. Xu, Y. Jia, Z. Wang, and M. Jiang, “Underdetermined Blind Source Separation for Sparse Signals Based on the Law of Large Numbers and Minimum Intersection Angle Rule”, Circuits Systems and Signal Processing, 39, 5, pp. 2442-2458 (2020).

3. [3] Y. Jia and P. Xu, “Convolutive Blind Source Separation for Communication Signals Based on the Sliding Z-Transform”, IEEE Access, 8, pp. 41213-41219 (2020).

4. [4] P. Xu and Y. Jia, “Blind source separation based on source number estimation and fast-ICA with a novel non-linear function”, Proceedings of the romanian academy series a-mathematics physics technical sciences information science, 21, 2, 93-194 (2020).

5. [5] D. D. Taralunga, I. Gussi, and R. Strungaru, “A new method for fetal electrocardiogram denoising using blind source separation and empirical mode decomposition”, Rev. Roum. Sci. Techn. - lectrotechn. Et nerg., 61, 1, pp. 94-98 (2016).

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