Browsing 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences by Subject "Backpropagation"

Now showing items 1-9 of 9

    • Article  

      AM-FM texture image analysis of the intima and media layers of the carotid artery 

      Loizou, Christos P.; Murray, V.; Pattichis, Marios S.; Christodoulou, C. S.; Pantzaris, Marios C.; Nicolaïdes, Andrew N.; Pattichis, Constantinos S. (2009)
      The purpose of this paper is to propose the use of amplitude modulation-frequency modulation (AM-FM) features for describing atherosclerotic plaque features that are associated with clinical factors such as intima media ...
    • Article  

      Congestion control in autonomous decentralized networks based on the lotka-volterra competition model 

      Antoniou, Pavlos Ch.; Pitsillides, Andreas (2009)
      Next generation communication networks are moving towards autonomous infrastructures that are capable of working unattended under dynamically changing conditions. The new network architecture involves interactions among ...
    • Conference Object  

      Convergence analysis for a class of neural networks 

      Polycarpou, Marios M.; Ioannou, Petros A. (Publ by IEEE, 1992)
      Summary form only given, as follows. The authors consider the convergence issue that arises in the application of backpropagation algorithms in a special class of neural network architectures, referred to as structured ...
    • Article  

      Genetics-based machine learning for the assessment of certain neuromuscular disorders 

      Pattichis, Constantinos S.; Schizas, Christos N. (1996)
      Clinical electromyography (EMG) provides useful information for the diagnosis of neuromuscular disorders. The utility of artificial neural networks (ANN's) in classifying EMG data trained with backpropagation or Kohonen's ...
    • Article  

      Learning and Convergence Analysis of Neural-Type Structured Networks 

      Polycarpou, Marios M.; Ioannou, Petros A. (1992)
      A special class of feedforward neural networks, referred to as structured networks, has recently been introduced as a method for solving matrix algebra problems in an inherently parallel formulation. In this paper we present ...
    • Conference Object  

      Modular artificial neural network valuation system 

      Panayiotou, Panayiotis A.; Pattichis, Constantinos S.; Jenkins, David; Plimmer, Frances (IEEE, 2000)
      The objective of this study was to design, develop and test a Modular Artificial Neural Network Valuation system (MANN) incorporating Multiple Regression Analysis (MRA) for the assessment of houses and apartments in Strovolos ...
    • Article  

      Multiagent reinforcement learning with spiking and non-spiking agents in the iterated prisoner's dilemma 

      Vassiliades, Vassilis; Cleanthous, A.; Christodoulou, Chris C. (2009)
      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 ...
    • Conference Object  

      A screening system for the assessment of opacity profusion in chest radiographs of miners with pneumoconiosis 

      Pattichis, Marios S.; Pattichis, Constantinos S.; Christodoulou, Christodoulos I.; James, D.; Ketai, L.; Soliz, P. (Institute of Electrical and Electronics Engineers Inc., 2002)
      The aim of this study was to develop a screening system of chest radiographs of miners with pneumoconiosis. Chest radiographs were of coal mine or silica dust exposed miners participating in a health screening program. A ...
    • Article  

      Sensitivity analysis of a neural network used for the forecasting of electric power load 

      Neocleous, Costas K.; Papazoglou, Thales M.; Schizas, Christos N.; Stratakis, Dimitrios I. (1999)
      A feedforward multilayer neural network has been used for the estimation of the four-hour-ahead electric load in Power Plant in the island of Crete. An attempt was made to use few variables for the input vector, while ...