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Contributions to independent component analysis, sensor array and complex valued signal processing

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Koivunen, Visa, Prof.
dc.contributor.author Ollila, Esa
dc.date.accessioned 2012-08-24T07:47:57Z
dc.date.available 2012-08-24T07:47:57Z
dc.date.issued 2010
dc.identifier.isbn 978-952-60-3031-9 (electronic)
dc.identifier.isbn 978-952-60-3030-2 (printed) #8195;
dc.identifier.issn 1797-4267
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/4748
dc.description.abstract Array and multichannel signal processing techniques are key technologies in wireless communications, radar, sonar and biomedical systems. In array signal processing, signals from multiple sources arrive simultaneously at a sensor array, so that each sensor array output contains a mixture of source signals. The multichannel output is then processed to provide information about the parameters of interest, e.g. the Direction-of-Arrival (DOA) of the source signals or the mixing system in the case of independent component analysis (ICA). Application areas include communications, radar, sonar and biomedicine. An important aspect is that the multichannel output is commonly complex-valued. In this thesis, new statistical procedures and several analytical results for array and multichannel signal processing are developed and derived. Also theoretical performance bounds of estimators are established. Experimental results showing reliable performance are given on all of the presented methods. In the area of array signal processing, the work concentrates on beamforming, high-resolution DOA estimation and estimation of the number of sources. The methods developed are robust in the sense that they are insensitive to largely deviating observations called outliers and to non-Gaussian noise environments. In the area of complex-valued ICA, we propose two new classes of demixing matrix estimators that add a new dimension of flexibility and versatility to complex-valued ICA since distinct estimators within the same class can have largely different statistical (robustness, accuracy) properties. Hence one can choose an estimator from the class that yields the best results to the specific application at hand. A simple closed form expression for the Cramér-Rao bound (CRB) is derived for demixing matrix estimation problem as well. Its usefulness is illustrated with a simulation study. In this thesis, the mathematical and statistical aspects of complex-valued signal processing are also addressed. Probability models, estimation bounds and novel statistics characterizing complex-valued signals are proposed. Specifically, complex elliptically symmetric (CES) distributions are proposed and studied, CRB for constrained and unconstrained complex-valued parameter estimation are derived, detectors of circularity are proposed and statistics such as circularity quotient and complex cumulants are derived. en
dc.format.extent Verkkokirja (1251 KB, 85 s.)
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto-yliopiston teknillinen korkeakoulu en
dc.relation.ispartofseries Report / Helsinki University of Technology, Department of Signal Processing and Acoustics,, 14 en
dc.relation.haspart [Publication 1]: Esa Ollila and Visa Koivunen. 2009. Complex ICA using generalized uncorrelating transform. Signal Processing, volume 89, number 4, pages 365-377. en
dc.relation.haspart [Publication 2]: Esa Ollila, Hannu Oja, and Visa Koivunen. 2008. Complex-valued ICA based on a pair of generalized covariance matrices. Computational Statistics & Data Analysis, volume 52, number 7, pages 3789-3805. en
dc.relation.haspart [Publication 3]: Esa Ollila, Hyon-Jung Kim, and Visa Koivunen. 2008. Compact Cramér–Rao bound expression for independent component analysis. IEEE Transactions on Signal Processing, volume 56, number 4, pages 1421-1428. © 2008 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 4]: Esa Ollila and Visa Koivunen. 2009. Influence function and asymptotic efficiency of scatter matrix based array processors: case MVDR beamformer. IEEE Transactions on Signal Processing, volume 57, number 1, pages 247-259. © 2008 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 5]: Esa Ollila and Visa Koivunen. 2003. Robust antenna array processing using M-estimators of pseudo-covariance. In: Gong Ke and Zhisheng Niu (editors). Proceedings of the 14th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2003). Beijing, China. 7-10 September 2003, volume 3, pages 2659-2663. © 2003 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 6]: Esa Ollila. 2008. On the circularity of a complex random variable. IEEE Signal Processing Letters, volume 15, pages 841-844. © 2008 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 7]: Esa Ollila and Visa Koivunen. 2009. Adjusting the generalized likelihood ratio test of circularity robust to non-normality. In: Proceedings of the 10th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2009). Perugia, Italy. 21-24 June 2009, pages 558-562. © 2009 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 8]: Jan Eriksson, Esa Ollila, and Visa Koivunen. 2009. Statistics for complex random variables revisited. In: Proceedings of the 34th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009). Taipei, Taiwan. 19-24 April 2009, pages 3565-3568. © 2009 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 9]: Esa Ollila, Visa Koivunen, and Jan Eriksson. 2008. On the Cramér-Rao bound for the constrained and unconstrained complex parameters. In: Proceedings of the 5th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2008). Darmstadt, Germany. 21-23 July 2008, pages 414-418. © 2008 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 10]: Esa Ollila and Visa Koivunen. 2004. Generalized complex elliptical distributions. In: Proceedings of the 3rd IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2004). Sitges, Spain. 18-21 July 2004, pages 460-464. © 2004 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.subject.other Electrical engineering
dc.subject.other Telecommunications engineering
dc.title Contributions to independent component analysis, sensor array and complex valued signal processing en
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.school Aalto-yliopiston teknillinen korkeakoulu fi
dc.contributor.department Signaalinkäsittelyn ja akustiikan laitos fi
dc.contributor.department Department of Signal Processing and Acoustics en
dc.subject.keyword independent component analysis en
dc.subject.keyword sensor array and complex valued signal processing en
dc.subject.keyword robust estimation en
dc.identifier.urn URN:ISBN:978-952-60-3031-9
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en
dc.contributor.supervisor Koivunen, Visa, Prof.


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