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In this letter, we introduce two approaches to estimate this dimension: one based on an information-theoretic criterion and the other based on hypothesis testing. We also present reduced-rank versions of these approaches that work for scenarios where the number of observations is comparable to or even smaller than the dimension of the data. Unlike other techniques for determining model orders, our techniques also work in the presence of additive colored noise."}],"citation":{"ama":"Hasija T, Lameiro C, Schreier PJ. Determining the dimension of the improper signal subspace in complex-valued data. <i>IEEE Signal Process Lett</i>. 2017;24:1606–1610.","bibtex":"@article{Hasija_Lameiro_Schreier_2017, title={Determining the dimension of the improper signal subspace in complex-valued data}, volume={24}, journal={IEEE Signal Process. 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