Abstract Background Artificial Neural Networks (ANNs) are introduced as robust and
versatile tools in quantitative structure-activity relationship (QSAR) modeling. Their …

In this paper, we propose a new biometric pattern recognition method. In classical
techniques only features of raw objects are compared. In our approach we will use …

The quality of models of systems and processes determines the effectiveness of numerous
contemporary technical systems ie, control systems, fault diagnosis systems or fault tolerant …

The application of computer modelling for medical purposes, although challenging, is a
promising pathway for further development in the medical sciences. We present predictive …

The aim of the paper is to present one, two and three-dimensional S-transforms. The paper
also shows the ability to study one, two and three-dimensional waveforms in frequency …

A major problem encountered by researchers of dynamic neural networks is the
computational complexity increasing the learning time. In this paper the parallel realization …

This paper explains and models selected associative processes that take place in biological
associative neural systems. Such associative systems allow us to form, expand, and exploit …

This paper focuses on a new kind of artificial neural networks–the Laplace transform artificial
neural networks (LTANN). It is proposed to use the Laplace transform instead of ordinary …

Two innovative systems based on feed-forward and recurrent neural network used for
qualitative analysis has been applied to specimens of different fruit tea. Their performance …

This paper presents two innovative evolutionary-neural systems based on feed-forward and
recurrent neural networks used for quantitative analysis. These systems have been applied …