This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
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...
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...
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...
—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...