Sciweavers

CSDA
2011
13 years 6 months ago
Approximate forward-backward algorithm for a switching linear Gaussian model
Motivated by the application of seismic inversion in the petroleum industry we consider a hidden Markov model with two hidden layers. The bottom layer is a Markov chain and given ...
Hugo Hammer, Håkon Tjelmeland
NPL
2000
112views more  NPL 2000»
13 years 11 months ago
Evolving Multilayer Perceptrons
Thispaper proposes anew version ofa method (G-Prop, geneticbackpropagation) that attempts to solve the problem of
Pedro A. Castillo Valdivieso, J. Carpio, Juan J. M...
IJON
2000
105views more  IJON 2000»
13 years 11 months ago
G-Prop: Global optimization of multilayer perceptrons using GAs
A general problem in model selection is to obtain the right parameters that make a model "t observed data. For a multilayer perceptron (MLP) trained with back-propagation (BP...
Pedro A. Castillo Valdivieso, Juan J. Merelo Guerv...
FLAIRS
2004
14 years 27 days ago
Hidden Layer Training via Hessian Matrix Information
The output weight optimization-hidden weight optimization (OWO-HWO) algorithm for training the multilayer perceptron alternately updates the output weights and the hidden weights....
Changhua Yu, Michael T. Manry, Jiang Li
FLAIRS
2004
14 years 27 days ago
Simulating Biological Motion Perception Using a Recurrent Neural Network
People have the ability to perceive biological motion under conditions of severely limited visual information. If the information is in the form of a point-light motion sequence o...
Roxanne L. Canosa
IJCNN
2000
IEEE
14 years 3 months ago
On Derivation of MLP Backpropagation from the Kelley-Bryson Optimal-Control Gradient Formula and Its Application
The well-known backpropagation (BP) derivative computation process for multilayer perceptrons (MLP) learning can be viewed as a simplified version of the Kelley-Bryson gradient f...
Eiji Mizutani, Stuart E. Dreyfus, Kenichi Nishio
ISNN
2005
Springer
14 years 5 months ago
FPGA Realization of a Radial Basis Function Based Nonlinear Channel Equalizer
In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is com...
Poyueh Chen, Hungming Tsai, ChengJian Lin, ChiYung...
IJCNN
2006
IEEE
14 years 5 months ago
Durability of Affordable Neural Networks against Damages
— In this study, we address the durability of the brain, which is able to operate in various imperfect situations. In our previous research, we have proposed a new network struct...
Yoko Uwate, Yoshifumi Nishio, Ruedi Stoop