Browsing by Subject "learning"

Now showing items 1-14 of 14

    • 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  

      Editorial 

      Lucas, P.; Rospars, J. -P; Christodoulou, Chris C. (2015)
    • Article  

      The effects of personality type in user-centered appraisal systems 

      Lekkas, Zacharias; Tsianos, Nikos; Germanakos, Panagiotis; Mourlas, Constantinos; Samaras, George S. (2011)
      The basic objective of this paper is to make an extensive reference of a combination of concepts and techniques coming from different research areas, Psychology and Web personalization technologies, both of which focus ...
    • Article  

      Learning optimisation by high firing irregularity 

      Cleanthous, A.; Christodoulou, Chris C. (2012)
      In a network of leaky integrate-and-fire (LIF) neurons, we investigate the functional role of irregular spiking at high rates. Irregular spiking is produced by either employing the partial somatic reset mechanism on every ...
    • 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  

      Medical content searching, retrieving, and sharing over the internet: Lessons learned from the meducator through a scenario-based evaluation 

      Antoniades, Athos; Nicolaidou, I.; Spachos, D.; Mylläri, J.; Giordano, D.; Dafli, E.; Mitsopoulou, E.; Schizas, Christos N.; Pattichis, Constantinos S.; Nikolaidou, M.; Bamidis, Panagiotis D. (2015)
      Background: The mEducator Best Practice Network (BPN) implemented and extended standards and reference models in e-learning to develop innovative frameworks as well as solutions that enable specialized state-of-the-art ...
    • Article  

      Modeling the effects of toxins in metabolic networks 

      Tamaddoni-Nezhad, A.; Chaleil, R.; Kakas, Antonis C.; Sternberg, M.; Nicholson, J.; Muggleton, S. (2007)
    • Article  

      Neural Network Models in EMG Diagnosis 

      Pattichis, Constantinos S.; Schizas, Christos N.; Middleton, Lefkos T. (1995)
      In the past years, several computer-aided quantitative motor unit action potential (MUAP) techniques were reported. It is now possible to add to these techniques the capability of automated medical diagnosis so that all ...
    • Article  

      On learning time delays between the spikes from different input neurons in a biophysical model of a pyramidal neuron 

      Koutsou, Achilleas; Bugmann, G.; Christodoulou, Chris C. (2015)
      Biological systems are able to recognise temporal sequences of stimuli or compute in the temporal domain. In this paper we are exploring whether a biophysical model of a pyramidal neuron can detect and learn systematic ...
    • Article  

      Personality and emotion as determinants of the learning experience: How affective behavior interacts with various components of the learning process 

      Lekkas, Zacharias; Germanakos, Panagiotis; Tsianos, Nikos; Mourlas, Constantinos; Samaras, George S. (2013)
      The aim of the present study is to develop a model that grasps the complexity of the concepts of personality and affect in a web-based learning environment. Furthermore, it presents the implications that these theoretical ...
    • Article  

      A spiking neuron model: Applications and learning 

      Christodoulou, Chris C.; Bugmann, G.; Clarkson, T. G. (2002)
      This paper presents a biologically inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the model as well as its applications in Computational ...
    • 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 ...
    • Article  

      A virtual emergency telemedicine serious game in medical training: A quantitative, professional feedback-informed evaluation study 

      Nicolaidou, I.; Antoniades, Athos; Constantinou, Renos; Marangos, C.; Kyriacou, Efthyvoulos C.; Bamidis, Panagiotis D.; Dafli, E.; Pattichis, Constantinos S. (2015)
      Background: Serious games involving virtual patients in medical education can provide a controlled setting within which players can learn in an engaging way, while avoiding the risks associated with real patients. Moreover, ...