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Browsing by Subject "artificial neural network"

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    • 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 ...

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