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» Computational Properties of Probabilistic Neural Networks
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JIRS
2008
100views more  JIRS 2008»
13 years 7 months ago
Model-based Predictive Control of Hybrid Systems: A Probabilistic Neural-network Approach to Real-time Control
Abstract This paper proposes an approach for reducing the computational complexity of a model-predictive-control strategy for discrete-time hybrid systems with discrete inputs only...
Bostjan Potocnik, Gasper Music, Igor Skrjanc, Boru...
IPPS
1998
IEEE
13 years 11 months ago
Using the BSP Cost Model to Optimise Parallel Neural Network Training
We derive cost formulae for three di erent parallelisation techniques for training supervised networks. These formulae are parameterised by properties of the target computer archit...
R. O. Rogers, David B. Skillicorn
SAC
2006
ACM
14 years 1 months ago
Facial emotion recognition by adaptive processing of tree structures
We present an emotion recognition system based on a probabilistic approach to adaptive processing of Facial Emotion Tree Structures (FETS). FETS are made up of localized Gabor fea...
Jia-Jun Wong, Siu-Yeung Cho
ICANN
2001
Springer
14 years 19 hour ago
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension
Abstract. It has remained an open question whether there exist product unit networks with constant depth that have superlinear VC dimension. In this paper we give an answer by cons...
Michael Schmitt
ECAI
2010
Springer
13 years 5 months ago
Continuous Conditional Random Fields for Regression in Remote Sensing
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Vladan Radosavljevic, Slobodan Vucetic, Zoran Obra...