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Coupled decompositions of multiple tensors are fundamental tools for multi-set data fusion. In this paper, we introduce a coupled version of the rank-(Lm, Ln, ·) block term decomposition (BTD), applicable to joint independent
subspace analysis. We propose two algorithms for its computation based on a coupled block simultaneous generalized Schur decomposition scheme. Numerical results are given to show the performance of the proposed algorithms.

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy consumer in buildings. Monitoring of the operation and energy consumption of HVAC would increase the awareness of building owners and maintenance service providers of the condition and quality of performance of these units, enabling conditioned-based maintenance which would help achieving high efficiency in energy consumption.