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» On Computing Functions with Uncertainty
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JAIR
1998
198views more  JAIR 1998»
13 years 8 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
ACIIDS
2009
IEEE
159views Database» more  ACIIDS 2009»
13 years 6 months ago
Application to GA-Based Fuzzy Control for Nonlinear Systems with Uncertainty
In this study, we strive to combine the advantages of fuzzy theory, genetic algorithms (GA), H tracking control schemes, smooth control and adaptive laws to design an adaptive fuzz...
Po-Chen Chen, Ken Yeh, Cheng-Wu Chen, Chen-Yuan Ch...
ICPR
2004
IEEE
14 years 10 months ago
Type-2 Fuzzy Hidden Markov Models to Phoneme Recognition
This paper presents a novel extension of Hidden Markov Models (HMMs): type-2 fuzzy HMMs (type-2 FHMMs). The advantage of this extension is that it can handle both randomness and f...
Jia Zeng, Zhi-Qiang Liu
ICASSP
2008
IEEE
14 years 3 months ago
Bayesian update of dialogue state for robust dialogue systems
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...
Blaise Thomson, Jost Schatzmann, Steve Young
DATE
2009
IEEE
92views Hardware» more  DATE 2009»
14 years 3 months ago
Using randomization to cope with circuit uncertainty
—Future computing systems will feature many cores that run fast, but might show more faults compared to existing CMOS technologies. New software methodologies must be adopted to ...
Hamid Safizadeh, Mohammad Tahghighi, Ehsan K. Arde...