Paper
7 June 1996 Spatiotemporal signal processing for blind separation of multichannel signals
Jitendra K. Tugnait
Author Affiliations +
Abstract
This paper is concerned with the problem of blind separation of independent signals (sources) from their linear convolutive mixtures. The problem consists of recovering the sources up to shaping filters from the observations of multiple-input multiple-output (MIMO) system output. The various signals are assumed to be linear but not necessarily i.i.d. (independent and identically distributed). The problem is cast into the framework of spatio-temporal equalization and estimation of the matrix impulse response function of MIMO channels (systems). An iterative, Godard cost based approach is considered for spatio-temporal equalization and MIMO impulse response estimation. Stationary points of the cost function are investigated and it is shown that all stable local minima correspond to desirable minima when doubly infinite equalizers are used. Analysis is also provided for the case when finite-length equalizers exist. The various input sequences are extracted and cancelled one-by-one. The matrix impulse response is then obtained by cross-correlating the extracted inputs with the observed outputs. Identifiability conditions are analyzed. Computer simulation examples are presented to illustrate the proposed approach.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jitendra K. Tugnait "Spatiotemporal signal processing for blind separation of multichannel signals", Proc. SPIE 2750, Digital Signal Processing Technology, (7 June 1996); https://doi.org/10.1117/12.241979
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Cited by 13 scholarly publications.
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KEYWORDS
Composites

Systems modeling

Autoregressive models

Sensors

Signal processing

Chemical elements

Filtering (signal processing)

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