Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138246
Title: A method based on L-BFGS to solve constrained complex-valued ICA
Authors: Nguyen, Anh Hai Trieu
Reju, V. G.
Khong, Andy Wai Hoong
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Nguyen, A. H. T., Reju, V. G., & Khong, A. W. H. (2019). A method based on L-BFGS to solve constrained complex-valued ICA. Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4370-4374. doi:10.1109/icassp.2019.8683698
Project: SLE-RP5
Abstract: Complex-valued independent component analysis (ICA) is a celebrated method in blind separation of complex-valued signals. In this paper, we propose to transform the constrained optimization problems of complex-valued ICA into unconstrained optimization problems which can be solved by limited-memory Broyden–Fletcher–Goldfarb–Shanno update (L-BFGS). As opposed to previous approaches, the proposed method does not apply any restriction on the Hessian matrix of ICA cost function. It can separate mixed sub-Gaussian, super-Gaussian, circular, and non-circular sources. Simulations show promising results.
URI: https://hdl.handle.net/10356/138246
DOI: 10.1109/ICASSP.2019.8683698
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICASSP.2019.8683698
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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