In this paper we consider the application of training with noise in multi-layer perceptron to input variables relevance determination. Noise injection is modiied in order to penalize irrelevant features. The proposed algorithm is attractive as it requires the tuning of a single parameter. This parameter controls the penalization of the inputs together with the complexity of the model. After the...

Robotica / Volume 32 / Issue 06 / September 2014, pp 935 952 DOI: 10.1017/S0263574713000982, Published online: 13 December 2013 Link to this article: http://journals.cambridge.org/abstract_S0263574713000982 How to cite this article: Avinesh Prasad, Bibhya Sharma and Jito Vanualailai (2014). A solution to the motion planning and control problem of a carlike robot via a single-layer perceptron. R...

Although the multi-layer perceptron (MLP) neural networks provide a lot of flexibility and have proven useful reliable in wide range classification regression problems, they still limitations. One most common is associated with optimization algorithm used to train them. The commonly training method stochastic gradient descent backpropagation (or for short) because it mathematically tractable (g...

A Bayesian implementation of learning in neural networks using Monte Carlo sampling has been developed by Neal (1996). This computation intensive method has shown encouraging performance in (Neal 1996) and in a study using several datasets in (Rasmussen 1996). For a full description of the method the reader is referred to (Neal 1996). Here a brief description of the algorithm will be given, alo...

A multilayer perceptron is a feed forward artificial neural network model that maps sets of input data onto a set of appropriate output. It is a modification of the standard linear perceptron in that it uses three or more layers of neurons (nodes) with nonlinear activation functions and is more powerful than the perceptron in that it can distinguish data that is not linearly separable, or separ...

strip tearing during cold rolling process has always been considered among the main concerns for steel companies. several works have been done so far regarding the examination of the issue. in this paper, experimental data from cold rolling tandem mill is used for detecting strip tearing. sensors are placed across the cold rolling tandem mill. they receive information on parameters (such as ang...

no unique method has been so far specified for determining the number of neurons in hidden layers of multi-layer perceptron (mlp) neural networks used for prediction. the present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. the data used in the present research for prediction are consumption data of water...

In this paper, we will consider the problem of classifying electroencephalogram (EEG) signals of normal subjects, and subjects suffering from psychiatric disorder, e.g., obsessive compulsive disorder, schizophrenia, using a class of artificial neural networks, viz., multi-layer perceptron. It is shown that the multilayer perceptron is capable of classifying unseen test EEG signals to a high deg...