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 ...
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...
The output weight optimization-hidden weight optimization (OWO-HWO) algorithm for training the multilayer perceptron alternately updates the output weights and the hidden weights....
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...
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...
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...
— 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...