Hypothesis Testing and Error Probability in Information Theory

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• Albert Guillén i Fàbregas, Universitat Pompeu Fabra
• Wednesday 04 November 2015, 11:30-12:30
• EEE Department, Room 503.

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Abstract: Two alternative exact characterizations of the minimal error probability of Bayesian M-ary hypothesis testing are reviewed. The first expression corresponds the error probability in an induced binary hypothesis test and implies the tightness of the meta-converse bound by Polyanskiy, Poor and Verdu; the second expression implies the tightness of a generalized Verdu-Han lower bound. The expressions help to characterise the minimal error probability of several problems in information theory and to identify the steps where existing converse bounds are loose.

Speaker Bio: Albert Guillén i Fàbregas is an ICREA Research Professor at the Department of Information and Communications Technologies, Universitat Pompeu Fabra, Barcelona, Spain. He is also a part-time Director of Research at the University of Cambridge, UK. In 1999 he received both the Telecommunication Engineering Degree and the Electronics Engineering Degree from Universitat Politècnica de Catalunya and the Politecnico di Torino respectively, and the PhD in Communication Systems from Ècole Polytechnique Fédérale de Lausanne in 2004. He has held appointments at the New Jersey Institute of Technology, Telecom Italia, European Space Agency, Institut Eurécom, University of South Australia and the University of Cambridge. He is a recipient of a Starting Grant of the European Research Council. He is Senior Member of the IEEE , Editor of the IEEE Transactions on Information Theory, Foundations and Trends in Communications and Information Theory and previously of the IEEE Transactions on Wireless Communications.

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