Identifiability in multi-channel factor analysis

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URI: https://hdl.handle.net/10902/32589
ISBN: 979-8-3503-2574-4
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Autoría
Stanton, Gray; Ramírez García, David; Santamaría Caballero, Luis IgnacioAutoridad Unican; Scharf, Louis L.Autoridad Unican; Wang, Haonan
Fecha
2023
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© 2023 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.
Publicado en
57th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 2023, 1344-1349
Editorial
Institute of Electrical and Electronics Engineers, Inc.
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Palabras clave
Factor analysis (FA)
Identifiability
Multi-channel factor analysis (MFA)
Resumen/Abstract
The recently developed Multi-Channel Factor Anal ysis (MFA) is a method for extracting a latent low-dimensional signal that is present across multiple channels and corrupted by unobserved single-channel interference and idiosyncratic noise. In MFA, only the channel structure and dimensionality of the signal and interference subspaces are specified in advance, which raises the concern that the signal, interference, and noise covariances may not be uniquely determined by the observation model. This paper presents necessary and sufficient conditions on the channel sizes and subspace dimensions to guarantee the identifiability of MFA, ensuring that the second-order spatial properties of the latent components can, in principle, be recovered from the multi-channel observations.
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