In this paper, we propose a way to apply Multi Layer Perceptron (MLP) to Functional Data Analysis. We introduce a computation model for functional input data and we show that this model is a well behaving extension of MLP: we show that the proposed model has the universal approximation property. Moreover, parameter estimation for this model is consistent. As a conclusion, we demonstrate functio...

It is easy for a multi-layered perception (MLP) to form open plane classification borders, and for a radial basis function network (RBFN) to form closed circular or elliptic classification borders. In contrast, it is difficult for a MLP to form closed circular or elliptic classification borders, and for RBFN to form open plane classification borders. Hence, MLP and RBFN have their own advantage...

Nowadays, computer scientists have shown the interest in the study of social insect’s behaviour in neural networks area for solving different combinatorial and statistical problems. Chief among these is the Artificial Bee Colony (ABC) algorithm. This paper investigates the use of ABC algorithm that simulates the intelligent foraging behaviour of a honey bee swarm. Multilayer Perceptron (MLP) tr...

MLP is a LIM-only protein of terminally differentiated striated muscle cells, where it accumulates at actin-based structures involved in cytoarchitecture organization. To assess its role in muscle differentiation, we disrupted the MLP gene in mice. MLP (-/-) mice developed dilated cardiomyopathy with hypertrophy and heart failure after birth. Ultrastructural analysis revealed dramatic disruptio...

This paper presents a new approach for automatic image color correction, based on statistical learning. The method both parameterizes color independently of illumination and corrects color for changes of illumination. The motivation for using a learning approach is to deal with changes of lighting typical of indoor environments such as home and office. The method is based on learning color inva...

This work continues in development of the recently proposed Bottle-Neck features for ASR. A five-layers MLP used in bottleneck feature extraction allows to obtai arbitrary feature size without dimensionality reduction by transforms, independently on the MLP training targets. The MLP topology – number and sizes of layers, suitable training targets, the impact of output feature transforms, the ne...