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NIPS
2003
13 years 9 months ago
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
Radford M. Neal, Matthew J. Beal, Sam T. Roweis
FORMATS
2006
Springer
13 years 11 months ago
Extended Directed Search for Probabilistic Timed Reachability
Current numerical model checkers for stochastic systems can efficiently analyse stochastic models. However, the fact that they are unable to provide debugging information constrain...
Husain Aljazzar, Stefan Leue
SBMF
2009
Springer
126views Formal Methods» more  SBMF 2009»
14 years 6 days ago
Undecidability Results for Distributed Probabilistic Systems
Abstract. In the verification of concurrent systems involving probabilities, the aim is to find out the maximum/minimum probability that a given event occurs (examples of such ev...
Sergio Giro
TWC
2011
291views more  TWC 2011»
13 years 2 months ago
On Optimal Cooperator Selection Policies for Multi-Hop Ad Hoc Networks
Abstract—In this paper we consider wireless cooperative multihop networks, where nodes that have decoded the message at the previous hop cooperate in the transmission toward the ...
Michele Rossi, Cristiano Tapparello, Stefano Tomas...
BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein