# Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis

@article{Cichocki2014TensorDF, title={Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis}, author={Andrzej Cichocki and Danilo P. Mandic and Lieven De Lathauwer and Guoxu Zhou and Qibin Zhao and Cesar F. Caiafa and A. Phan}, journal={IEEE Signal Processing Magazine}, year={2014}, volume={32}, pages={145-163} }

The widespread use of multisensor technology and the emergence of big data sets have highlighted the limitations of standard flat-view matrix models and the necessity to move toward more versatile data analysis tools. We show that higher-order tensors (i.e., multiway arrays) enable such a fundamental paradigm shift toward models that are essentially polynomial, the uniqueness of which, unlike the matrix methods, is guaranteed under very mild and natural conditions. Benefiting from the power of…

## 1,096 Citations

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