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FLAIRS
2008
14 years 17 days ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
ICASSP
2011
IEEE
13 years 2 months ago
A non-negative approach to semi-supervised separation of speech from noise with the use of temporal dynamics
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
Gautham J. Mysore, Paris Smaragdis
NIPS
2007
13 years 11 months ago
An in-silico Neural Model of Dynamic Routing through Neuronal Coherence
We describe a neurobiologically plausible model to implement dynamic routing using the concept of neuronal communication through neuronal coherence. The model has a three-tier arc...
Devarajan Sridharan, Brian Percival, John V. Arthu...
VLSID
2004
IEEE
142views VLSI» more  VLSID 2004»
14 years 10 months ago
Dynamic Noise Margin: Definitions and Model
Dynamic noise analysis is greatly needed in place of traditional static noise analysis due to the ever increasingly stringent design requirement for VLSI chips based on very deep ...
Li Ding 0002, Pinaki Mazumder
TSMC
2010
13 years 5 months ago
Automated Modeling of Dynamic Reliability Block Diagrams Using Colored Petri Nets
Computer system reliability is conventionally modeled and analyzed using techniques such as fault tree analysis (FTA) and reliability block diagrams (RBD), which provide static rep...
Ryan Robidoux, Haiping Xu, Liudong Xing, MengChu Z...