{"volume":24,"language":[{"iso":"eng"}],"status":"public","intvolume":" 24","date_updated":"2023-01-30T12:08:06Z","page":"1606–1610","year":"2017","citation":{"short":"T. Hasija, C. Lameiro, P.J. Schreier, IEEE Signal Process. Lett. 24 (2017) 1606–1610.","chicago":"Hasija, Tanuj, Christian Lameiro, and Peter J. Schreier. “Determining the Dimension of the Improper Signal Subspace in Complex-Valued Data.” IEEE Signal Process. Lett. 24 (2017): 1606–1610.","mla":"Hasija, Tanuj, et al. “Determining the Dimension of the Improper Signal Subspace in Complex-Valued Data.” IEEE Signal Process. Lett., vol. 24, 2017, pp. 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. Lett.}, author={Hasija, Tanuj and Lameiro, Christian and Schreier, Peter J.}, year={2017}, pages={1606–1610} }","ieee":"T. Hasija, C. Lameiro, and P. J. Schreier, “Determining the dimension of the improper signal subspace in complex-valued data,” IEEE Signal Process. Lett., vol. 24, pp. 1606–1610, 2017.","apa":"Hasija, T., Lameiro, C., & Schreier, P. J. (2017). Determining the dimension of the improper signal subspace in complex-valued data. IEEE Signal Process. Lett., 24, 1606–1610.","ama":"Hasija T, Lameiro C, Schreier PJ. Determining the dimension of the improper signal subspace in complex-valued data. IEEE Signal Process Lett. 2017;24:1606–1610."},"author":[{"first_name":"Tanuj","id":"43497","full_name":"Hasija, Tanuj","last_name":"Hasija"},{"first_name":"Christian","full_name":"Lameiro, Christian","last_name":"Lameiro"},{"first_name":"Peter J.","last_name":"Schreier","full_name":"Schreier, Peter J."}],"title":"Determining the dimension of the improper signal subspace in complex-valued data","department":[{"_id":"263"}],"type":"journal_article","publication":"IEEE Signal Process. Lett.","date_created":"2023-01-30T11:51:41Z","abstract":[{"lang":"eng","text":"Abstract: A complex-valued signal is improper if it is correlated with its complex conjugate. The dimension of the improper signal subspace, i.e., the number of improper components in a complex-valued measurement, is an important parameter and is unknown in most of the applications. 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."}],"user_id":"43497","_id":"40711"}