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NN
2010
Springer
225views Neural Networks» more  NN 2010»
13 years 7 months ago
Learning to imitate stochastic time series in a compositional way by chaos
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Jun Namikawa, Jun Tani
ICASSP
2011
IEEE
13 years 8 days ago
Comparative threshold performance study for conditional and unconditional direction-of-arrival estimation
Comparative analysis of the threshold SNR and/or sample support values where genuine maximum likelihood DOA estimation starts to produce “outliers” is conducted for unconditio...
Yuri I. Abramovich, Ben A. Johnson
BMCBI
2008
93views more  BMCBI 2008»
13 years 8 months ago
Hybrid MM/SVM structural sensors for stochastic sequential data
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Brian Roux, Stephen Winters-Hilt
RP
2009
Springer
110views Control Systems» more  RP 2009»
14 years 3 months ago
Formalisms for Specifying Markovian Population Models
Abstract. We compare several languages for specifying Markovian population models such as queuing networks and chemical reaction networks. These languages —matrix descriptions, s...
Thomas A. Henzinger, Barbara Jobstmann, Verena Wol...
ICALP
2009
Springer
14 years 8 months ago
Rate-Based Transition Systems for Stochastic Process Calculi
A variant of Rate Transition Systems (RTS), proposed by Klin and Sassone, is introduced and used as the basic model for defining stochastic behaviour of processes. The transition r...
Rocco De Nicola, Diego Latella, Michele Loreti, Mi...