Browsing by Subject "artificial neural network"

Article

Autoregressive and cepstral analyses of motor unit action potentials

Pattichis, Constantinos S.; Elia, Andreas G. (1999)

Quantitative electromyographic signal analysis in the time domain for motor unit action potential (MUAP) classification and disease identification has been well documented over recent years. Considerable work has also been ...

Article

Behavioral plasticity through the modulation of switch neurons

Vassiliades, Vassilis; Christodoulou, Chris C. (2016)

A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by ...

Article

Characterization of the traditional Cypriot spirit Zivania by means of Counterpropagation Artificial Neural Networks

Ballabio, D.; Kokkinofta, Rebecca I.; Todeschini, R.; Theocharis, Charis R. (2007)

Multivariate chemometric techniques, such as Principal Component Analysis and Discriminant Analysis, were previously used to determine the authenticity of the Cypriot traditional spirit Zivania, but these techniques revealed ...

Article

Classification capacity of a modular neural network implementing neurally inspired architecture and training rules

Poirazi, Panayiota; Neocleous, Costas K.; Pattichis, Constantinos S.; Schizas, Christos N. (2004)

A three-layer neural network (NN) with novel adaptive architecture has been developed. The hidden layer of the network consists of slabs of single neuron models, where neurons within a slab-but not between slabs- have the ...

Article

Classification of rainfall variability by using artificial neural networks

Michaelides, Silas C.; Pattichis, Constantinos S.; Kleovoulou, Georgia (2001)

In this paper, the usefulness of artificial neural networks (ANNs) as a suitable tool for the study of the medium and long-term climatic variability is examined. A method for classifying the inherent variability of climate ...

Article

Comparing Different Classifiers for Automatic Age Estimation

Lanitis, A.; Draganova, C.; Christodoulou, Chris C. (2004)

We describe a quantitative evaluation of the performance of different classifiers in the task of automatic age estimation. In this context, we generate a statistical model of facial appearance, which is subsequently used ...

Article

Computer-aided classification of breast cancer nuclei

Schnorrenberg, F.; Pattichis, Constantinos S.; Schizas, Christos N.; Kyriacou, Kyriacos C.; Vassiliou, M. (1996)

Breast cancer is the most common malignancy affecting the female population in industrialized countries. Prognostic factors, such as steroid receptors visualized in biopsy slides, provide critical information to oncologists ...

Article

Distinguishing the causes of firing with themembrane potential slope

Koutsou, Achilleas; Christodoulou, Chris C.; Bugmann, G.; Kanev, J. (2012)

In this letter, we aim to measure the relative contribution of coincidence detection and temporal integration to the firing of spikes of a simple neuron model. To this end, we develop a method to infer the degree of synchrony ...

Article

Does high firing irregularity enhance learning?

Christodoulou, Chris C.; Cleanthous, A. (2011)

In this note, we demonstrate that the high firing irregularity produced by the leaky integrate-and-fire neuron with the partial somatic reset mechanism, which has been shown to be the most likely candidate to reflect the ...

Article

Dynamical neural networks that ensure exponential identification error convergence

Kosmatopoulos, E. B.; Christodoulou, Manolis A.; Ioannou, Petros A. (1997)

Classical adaptive and robust adaptive schemes, are unable to ensure convergence of the identification error to zero, in the case of modeling errors. Therefore, the usage of such schemes to 'black-box' identification of ...

Article

An embedded saliency map estimator scheme: Application to video encoding

Tsapatsoulis, Nicolas; Rapantzikos, K.; Pattichis, Constantinos S. (2007)

In this paper we propose a novel saliency-based computational model for visual attention. This model processes both top-down (goal directed) and bottom-up information. Processing in the top-down channel creates the so ...

Article

First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach

Neocleous, Andreas C.; Nicolaides, Kypros H.; Schizas, Christos N. (2016)

The objective of this study is to examine the potential value of using machine learning techniques such as artificial neural network (ANN) schemes for the noninvasive estimation, at 11-13 weeks of gestation, the risk for ...

Article

Improved detection of breast cancer nuclei using modular neural networks

Schnorrenberg, F.; Tsapatsoulis, Nicolas; Pattichis, Constantinos S.; Schizas, Christos N.; Kollias, S.; Vassiliou, M.; Adamou, Adamos K.; Kyriacou, Kyriacos C. (2000)

A modular neural network-based approach to detect and classify breast cancer nuclei stained for steroid receptors in hispathological sections is evaluated. The system named biopsy analysis support system (BASS) is designed ...

Article

Is self-control a learned strategy employed by a reward maximizing brain?

Cleanthous, A.; Christodoulou, Chris C. (2009)

Article

Learning systems in biosignal analysis

Schizas, Christos N.; Pattichis, Constantinos S. (1997)

In biosignal analysis, the utility of artificial neural networks (ANN) in classifying electromyographic (EMG) data trained with the momentum back propagation algorithm has recently been demonstrated. In the current study, ...

Article

Ligand - Based virtual screening procedure for the prediction and the identification of novel β-amyloid aggregation inhibitors using Kohonen maps and Counterpropagation Artificial Neural Networks

Afantitis, Antreas; Melagraki, G.; Koutentis, Panayiotis Andreas; Sarimveis, H.; Kollias, G. (2011)

In this work we have developed an in silico model to predict the inhibition of β-amyloid aggregation by small organic molecules. In particular we have explored the inhibitory activity of a series of 62 N-phenylanthranilic ...

Article

Multiagent reinforcement learning: Spiking and nonspiking agents in the Iterated Prisoner's Dilemma

Vassiliades, Vassilis; Cleanthous, A.; Christodoulou, Chris C. (2011)

This paper investigates multiagent reinforcement learning (MARL) in a general-sum game where the payoffs' structure is such that the agents are required to exploit each other in a way that benefits all agents. The contradictory ...

Article

Synoptic classification and establishment of analogues with artificial neural networks

Michaelides, Silas C.; Liassidou, F.; Schizas, Christos N. (2007)

Weather charts depicting the spatial distribution of various meteorological parameters constitute an indispensable pictorial tool for meteorologists, in diagnosing and forecasting synoptic conditions and the associated ...

Article

Time-scale analysis of motor unit action potentials

Pattichis, Constantinos S.; Pattichis, Marios S. (1999)

Quantitative analysis in clinical electromyography (EMG) is very desirable because it allows a more standardized, sensitive and specific evaluation of the neurophysiological findings, especially for the assessment of ...

Article

Toward nonlinear local reinforcement learning rules through neuroevolution

Vassiliades, Vassilis; Christodoulou, Chris C. (2013)

We consider the problem of designing local reinforcement learning rules for artificial neural network (ANN) controllers. Motivated by the universal approximation properties of ANNs, we adopt an ANN representation for the ...