Stochastic and Deterministic Tensorization for Blind Signal Separation [PDF]
Latent Variable Analysis and Signal Separation, 2015 Given an instantaneous mixture of some source signals, the blind signal separation BSS problem consists of the identification of both the mixing matrix and the original sources. By itself, it is a non-unique matrix factorization problem, while unique solutions can be obtained by imposing additional assumptions such as statistical independence.
Debals, Otto, De Lathauwer, Lieven
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Towards interpretable classifiers with blind signal separation [PDF]
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012 Blind signal separation (BSS) is a powerful tool to open-up complex signals into component sources that are often interpretable. However, BSS methods are generally unsupervised, therefore the assignment of class membership from the elements of the mixing matrix may be sub-optimal.
Ruiz, Hector +6 more
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Signal Separation Operator Based on Wavelet Transform for Non-Stationary Signal Decomposition [PDF]
SensorsThis paper develops a new frame for non-stationary signal separation, which is a combination of wavelet transform, clustering strategy and local maximum approximation.
Ningning Han, Yongzhen Pei, Zhanjie Song
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From blind signal extraction to blind instantaneous signal separation: criteria, algorithms, and stability [PDF]
IEEE Transactions on Neural Networks, 2004 S. Cruces, A. Cichocki, S. Amari
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Underdetermined Blind Source Separation of Audio Signals for Group Reared Pigs Based on Sparse Component Analysis [PDF]
SensorsIn order to solve the problem of difficult separation of audio signals collected in pig environments, this study proposes an underdetermined blind source separation (UBSS) method based on sparsification theory.
Weihao Pan +5 more
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Performing Nonlinear Blind Source Separation With Signal Invariants [PDF]
, 2009 Given a time series of multicomponent measurements x(t), the usual objective of nonlinear blind source separation (BSS) is to find a "source" time series s(t), comprised of statistically independent combinations of the measured components. In this paper,
David Levin
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Relevance of polynomial matrix decompositions to broadband blind signal separation [PDF]
Signal Processing, 2017 The polynomial matrix EVD (PEVD) is an extension of the conventional eigenvalue decomposition (EVD) to polynomial matrices. The purpose of this article is to provide a review of the theoretical foundations of the PEVD and to highlight practical ...
Soydan Redif +2 more
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Accelerated Conjugate Gradient for Second-Order Blind Signal Separation
Acoustics, 2022 This paper proposes a new adaptive algorithm for the second-order blind signal separation (BSS) problem with convolutive mixtures by utilising a combination of an accelerated gradient and a conjugate gradient method.
Hai Huyen Dam, Sven Nordholm
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Blind source separation algorithm for complex signals in noise
Dianzi Jishu Yingyong, 2022 Complex signal analysis is one of the common problems in signal processing technology. In blind signal separation technology, especially convolution mixing problem or frequency domain analysis, it is necessary to establish the corresponding complex value
Feng Pingxing, Zhang Hongbo, Li Wenxiang
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JCCM: Joint conformer and CNN model for overlapping radio signals recognition
Electronics Letters, 2023 Overlapping radio signals recognition is attracting more attention as the development and ubiquitous application of radio technologies. The traditional blind signal separation (BSS) method is mostly not effective when both radio propagation effects and ...
Junbin Liang +5 more
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