Single Channel Blind Source Separation Using Dual Extended Kalman Filter

Dutt, Rashi and Mondal, Sayon and Acharyya, Amit (2021) Single Channel Blind Source Separation Using Dual Extended Kalman Filter. In: 53rd IEEE International Symposium on Circuits and Systems, ISCAS 2021, 22 May 2021 through 28 May 2021, Daegu.

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Abstract

Single channel Blind Source Separation (SCBSS) is an important source separation technique gaining prominence in many emerging applications. It is a special case of the well-defined Blind Source Separation (BSS) where only a single mixed signal is recorded to estimate the unknown sources. In this paper, we propose a simultaneous state-parameter estimation methodology for SCBSS using Dual Extended Kalman Filter (D-EKF). The proposed methodology eliminates the inherent frequency disjoint and statistical independence limitations of the state-of-the-art SCBSS approaches such as single channel Independent Component Analysis (SCICA). A frame-based Kalman processing technique has been proposed to ensure faster convergence of the proposed methodology. Simulation results have been presented for mixed sources with overlapping spectra and compared with SCICA and other BSS algorithms. The results demonstrate the superior performance of the proposed methodology with improved Signal-to-Interference Ratio (SIR) and Signal-to-Distortion Ratio (SDR) for real-world practical applications. © 2021 IEEE

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IITH Creators:
IITH CreatorsORCiD
Acharyya, Amithttp://orcid.org/0000-0002-5636-0676
Item Type: Conference or Workshop Item (Paper)
Additional Information: Dutt and Acharyya acknowledge the Intel India Research Fellowship - 2020. This work is also partly supported by the Department of Science & Technology (DST) under the Internet of Things (IoT) Research of Interdisciplinary Cyber Physical Systems (ICPS) Pro-gramme, Government of India (GOI), with the project entitled “IOT Based Holistic Prevention and Prediction of CVD (i-PREACT).” CAD Tools are supported under the Ministry of Electronics and Information technology (MeitY) SMDP-C2S Program, GOI.
Uncontrolled Keywords: Dual extended kalman filter; Single channel blind source separation; Single channel independent component analysis; State-parameter estimation
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 26 Sep 2022 08:54
Last Modified: 26 Sep 2022 08:54
URI: http://raiith.iith.ac.in/id/eprint/10709
Publisher URL: http://doi.org/10.1109/ISCAS51556.2021.9401796
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