GLOBECOM
2006
IEEE
14 years 6 months ago
2006
IEEE
— This paper presents an analytical model for the analysis of Hybrid ARQ techniques on Discrete Time Markov Channels by means of Markov chains. The first contribution is an orig...
GLOBECOM
2006
IEEE
14 years 6 months ago
2006
IEEE
— A novel method is proposed for reducing the feedback rate of a transmit beamforming system with feedback of quantized channel state information. Specifically, the channel is m...
TACAS
2007
Springer
14 years 7 months ago
2007
Springer
This paper studies the effect of bisimulation minimisation in model checking of monolithic discrete-time and continuous-time Markov chains as well as variants thereof with rewards...
EPEW
2007
Springer
14 years 7 months ago
2007
Springer
We consider a class of Markov chains known for its closed form transient and steady-state distributions. We show that some absorbing chains can be also seen as members of this clas...
IEEEARES
2007
IEEE
14 years 7 months ago
2007
IEEE
Security communication systems composed of highly reliable components may have few if any failures while undergoing heavy testing or field-usage. This paper combines (i) analysis ...
IROS
2008
IEEE
14 years 7 months ago
2008
IEEE
— Robots acting in populated environments must be capable of safe but also time efficient navigation. Trying to completely avoid regions resulting from worst case predictions of...
CDC
2008
IEEE
14 years 7 months ago
2008
IEEE
— In this paper we discuss the consensus problem for a network of dynamic agents with undirected information flow and random switching topologies. The switching is determined by...
ICC
2009
IEEE
14 years 7 months ago
2009
IEEE
—We introduce a 3-dimensional Markov chain that integrates the IEEE 802.11 DCF contention resolution and queueing processes into one model. Important QoS measures, delay and loss...
ICC
2009
IEEE
14 years 7 months ago
2009
IEEE
— In this paper, we introduce a novel Markov Chain (MC) representation aided Minimum Bit Error Rate (MBER) detection method that is applicable to an M-QAM modulated SDM/SDMA upli...
ICML
2009
IEEE
14 years 7 months ago
2009
IEEE
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...