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IJCNN
2000
IEEE
15 years 7 months ago
On MCMC Sampling in Bayesian MLP Neural Networks
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Aki Vehtari, Simo Särkkä, Jouko Lampinen
CEC
2007
IEEE
15 years 7 months ago
A Simulated Evolution-Tabu search hybrid metaheuristic for routing in computer networks
Routing in computer networks is a nonlinear combinatorial optimization problem with numerous constraints and is classified as an NP-complete problem. There are certain important Qo...
Salman A. Khan, Zubair A. Baig
NIPS
1996
15 years 4 months ago
Radial Basis Function Networks and Complexity Regularization in Function Learning
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Adam Krzyzak, Tamás Linder
137
Voted
JUCS
2007
107views more  JUCS 2007»
15 years 3 months ago
Genetic Algorithm Based Recurrent Fuzzy Neural Network Modeling of Chemical Processes
: A genetic algorithm (GA) based recurrent fuzzy neural network modeling method for dynamic nonlinear chemical process is presented. The dynamic recurrent fuzzy neural network (RFN...
Jili Tao, Ning Wang, Xuejun Wang
CDC
2008
IEEE
109views Control Systems» more  CDC 2008»
15 years 10 months ago
LQG control over lossy TCP-like networks with probabilistic packet acknowledgements
Abstract— This paper is concerned with control applications over lossy data networks. Sensor data is transmitted to an estimation-control unit over a network, and control command...
Emanuele Garone, Bruno Sinopoli, Alessandro Casavo...