Single hidden layer feedforward neural networks (SLFNs) with fixed weights possess the universal approximation property provided that approximated functions are univariate. But this phenomenon does not lay any restrictions on the number of neurons in the hidden layer. The more this number, the more the probability of the considered network to give precise results. In this note, we constructivel...

A new derivation is presented for the bounds on the size of a multilayer neural network to exactly implement an arbitrary training set; namely the training set can be implemented with zero error with two layers and with the number of the hidden-layer neurons equal to #1>/= p-1. The derivation does not require the separation of the input space by particular hyperplanes, as in previous derivation...

We consider feed-forward neural networks with one non-linear hidden layer and linear output units. The transfer function in the hidden layer are either bell-shaped or sigmoid. In the bell-shaped case, we show how Bernstein polynomials on one hand and the theory of the heat equation on the other are relevant for understanding the properties of the corresponding networks. In particular, these tec...

Neural networks have been massively used in regression problems due to their ability to approximate complex nonlinear mappings directly from input patterns. However, collected data for training networks often include outliers which affect final results. This paper presents an approach for training single hidden-layer feedforward neural networks (SLFNs) using weighted least-squares scheme which ...

We present a closed form expression for initializing the input weights in a multilayer perceptron, which can be used as the first step in synthesis of an Extreme Learning Machine. The expression is based on the standard function for a separating hyperplane as computed in multilayer perceptrons and linear Support Vector Machines; that is, as a linear combination of input data samples. In the abs...

Technological innovation talent is the core element of economic and social development. It is a symbol of a country's soft power reflected from the perspective of knowledge. Therefore it is theoretically valuable and practically significant for a country to evaluate the comprehensive level technological innovation. Based on the construction of evaluation index system of the technological innova...

groundwater quality management is the most important issue in many arid and semi-arid countries, including iran.artificial neural network (ann) has an extensive range of applications in water resources management. in this study,artificial neural network was developed using matlab r2013 software package, and cl, ec, so4 and no3 qualitativeparameters were estimated and compared with the measured ...

This paper introduces a flexible neural tree (FNT) with necessary number of hidden units and is generated initially as a flexible multi-layer feed-forward neural network evolved using an evolutionary procedure and also considers the approximation of sufficiently smooth multivariable function with a multilayer perceptron. For a given neural tree with approximation order, explicit formulas for th...

production of several yeast products occur in presence of mixtures of monosaccharides. to study effect of xylose and glucose mixtures with system aeration and nitrogen source as the other two operative variables on xylitol production by pichia guilliermondii, the present work was defined. artificial neural network (ann) strategy was used to athematically show interplay between these three contr...

Table 1: Phoneme recognition rates for diierent hybrid RBF-HMM systems; all values in %. In line two the results for a NN with one additional hidden layer of 100 sigmoidal units are depicted. The recognition rates for both training procedures are inferior to the net without hidden layer. This is mainly contributed to the relatively small hidden layer with 100 nodes, which acts like a bottleneck...