Search Results - "Barembruch, S."
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1
On Approximate Maximum-Likelihood Methods for Blind Identification: How to Cope With the Curse of Dimensionality
Published in IEEE transactions on signal processing (01-11-2009)“…We discuss approximate maximum-likelihood methods for blind identification and deconvolution. These algorithms are based on particle approximation versions of…”
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Journal Article -
2
A sparse EM algorithm for blind and semi-blind identification of doubly selective OFDM channels
Published in 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (01-06-2010)“…In recent years many sparse estimation methods, also known as compressed sensing, have been developed for channel identification problems in digital…”
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Conference Proceeding
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A comparison of approximate Viterbi techniques and particle filtering for data estimation in digital communications
Published in 2010 IEEE International Conference on Acoustics, Speech and Signal Processing (01-03-2010)“…We consider trellis-based algorithms for data estimation in digital communication systems. We present a general framework which includes approximate Viterbi…”
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Conference Proceeding -
4
On approximate maximum likelihood methods for blind identification: How to copewith the curse of dimensionality
Published in 2008 IEEE 9th Workshop on Signal Processing Advances in Wireless Communications (01-07-2008)“…We discuss approximate maximum likelihood methods for blind identification and deconvolution. These algorithms are based on particle approximation versions of…”
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Conference Proceeding -
5
Maximum likelihood blind deconvolution for sparse systems
Published in 2010 2nd International Workshop on Cognitive Information Processing (01-06-2010)“…In recent years many sparse estimation methods, also known as compressed sensing, have been developed for channel identification problems in digital…”
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Conference Proceeding -
6
On optimal sampling for particle filtering in digital communication
Published in 2008 IEEE 9th Workshop on Signal Processing Advances in Wireless Communications (01-07-2008)“…Particle filtering has been successfully used to approximate the fixed-lag or fixed-interval smoothing distributions in digital communication and to perform…”
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Conference Proceeding -
7
The Expectation and Sparse Maximization Algorithm
Published in Journal of communications and networks (2010)“…In recent years, many sparse estimation methods, also known as compressed sensing, have been developed. However, most of these methods presume that the…”
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Journal Article