This work concerns testing the number of parameters in one hidden layer multilayer perceptron (MLP). For this purpose we assume that we have identifiable models, up to a finite group of transformations on the weights, this is for example the case when the number of hidden units is know. In this framework, we show that we get a simple asymptotic distribution, if we use the logarithm of the deter...

In this paper we tackle the problem of unconstrained handwritten character recognition using different classification strategies. For such an aim, four multilayer perceptron classifiers (MLP) are built and used into three different classification strategies: combination of two 26– class classifiers; a 26–metaclass classifier and a 52– class classifier. Experimental results on the NIST SD19 data...

In recent years, the cryptographic community has explored new approaches of power analysis based on machine learning models such as Support Vector Machine (SVM), MultiLayer Perceptron (MLP) or Random Forest (RF). Realized experiments proved that the method based on MLP can provide almost 100% success rate after optimization. Nevertheless, this description of results is based on the first order ...

This study reports on the development of a diagnostic expert system – incorporating a multilayer perceptron (MLP) – designed to identify any sub-type of dysarthria (loss of neuromuscular control over the articulators) manifested by a patient undergoing a Frenchay Dysarthria Assessment (FDA) evaluation. If sufficient information is provided describing pathological features of the patient’s speec...

This paper discusses the empirical evaluation of improving generalization performance of neural networks by systematic treatment of training and test failures. As a result of systematic treatment of failures, multilayer perceptron (MLP) discriminants were developed as discrimination techniques. The experiments presented in this paper illustrate the application of discrimination techniques using...

Mapping knowledge structures is a key task in Knowledge Discovery in Databases (KDD). In order to display the thematic organization of knowledge, we compare and evaluate two different cartography approaches: principal components analysis (PCA) and a multilayer perceptron (MLP) in "self-association" mode. This kind of MLP can be used to perform a PCA when the activation function is set to the id...

The performance of global affine and nonlinear transformations for speaker adaptation in a hidden Markov model (HMM) speech recognition system are compared in this paper. The nonlinear transformation was obtained with a multilayer perceptron network (MLP) which was trained during the adaptation process to transform the mean vectors of the HMMs such that the output probabilities of the HMMs for ...

Considering the grid manager's point of view,needsin terms ofprediction of intermittent energy like thephotovoltaic resourcecan be distinguishedaccording to theconsideredhorizon: following days (d+1, d+2 and d+3), next day by hourly step (h+24), next hour (h+1) and next few minutes (m+5 e.g.). Through this work, we haveidentified methodologies using time series modelsfor thepredictionhorizonof ...

The multilayer perceptron (MLP) is a well established neural network model for supervised learning problems. Furthermore, it is well known that its performance for a given problem depends crucially on appropriately selecting the MLP architecture, which is typically achieved using cross-validation. In this work, we propose an incremental Bayesian methodology to address the important problem of a...