A method based on L-BFGS to solve constrained complex-valued ICA

A method based on L-BFGS to solve constrained complex-valued ICA

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...

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Bibliographic Details
Main Authors: Nguyen, Anh Hai Trieu, Reju, V. G., Khong, Andy Wai Hoong
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Engineering::Electrical and electronic engineering
Complex-valued ICA
L-BFGS
Online Access:https://hdl.handle.net/10356/138246
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Institution: Nanyang Technological University
Language: English
Description
Summary: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.

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