Independent Vector Analysis: An Extension of ICA to Multivariate Components

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Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation (2018, background): “tistical separability of the target and interfering sources. This aspect, however, limits their applicability when all the sources are speech signals and therefore have similar statistical properties [35], [36], [37], [38]. Beyond ICA methods, several recent studies have investigated the feasibility”
Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects (2015, background): “P (m) = P that applies to all the involved mixtures [82], [109].”
Stable and fast update rules for independent vector analysis based on auxiliary function technique (2011, background): “Index Terms— independent vector analysis, blind source separation, natural gradient, auxiliary function”
Determined Blind Source Separation Unifying Independent Vector Analysis and Nonnegative Matrix Factorization (2016, methodology): “In summary, FDICA+DOA is severely affected by the spatial conditions rather than source modeling, whereas IVA and determined rank-1 MNMF are not.”