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Fast Time-Invariant Implementations of Gaussian Signal Detectors
Stanford University, CA, USA.
Massachusetts Institute of Technology, MA, USA.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Stanford University, CA, USA.
1978 (English)In: IEEE Transactions on Information Theory, ISSN 0018-9448, Vol. 24, no 4, 469-477 p.Article in journal (Refereed) Published
Abstract [en]

A new implementation is presented for the optimum likelihood ratio detector for stationary Gaussian signals in white Gaussian noise that uses only two causal time-invariant filters. This solution also has the advantage that fast algorithms based on the Levinson and Chandrasekhar equations can he used for the determination of these time-invariant filters. By using a notion of "closeness to stationarity,' there is a natural extension of the above results for nonstationary signal processes.

Place, publisher, year, edition, pages
IEEE Information Theory Society , 1978. Vol. 24, no 4, 469-477 p.
Keyword [en]
Gaussian processes, Signal detection, Stochastic, Chandrasekhar equations
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-100997DOI: 10.1109/TIT.1978.1055907OAI: diva2:664717
Available from: 2013-11-16 Created: 2013-11-16 Last updated: 2013-11-16

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ReferencesLink to record
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