Neural network modeling of an ionospheric process: temporal and spatial forecasting of the critical frequencies

Kumluca, Ayça


Neural network based forecasting for telecommunications via ionosphere
Şenalp, Erdem Türker; Tulunay, Ersin; Tulunay, Yurdanur; Department of Electrical and Electronics Engineering (2001)
Neural network techniques in electromagnetic target classification: A comparison study
Sayan, Gönül (1999-01-01)
The performances of a self-organizing map classifier, a multilayer perceptron classifier and a conventional classifier, based on the well-known principal component analysis technique, are compared in classifying a group of model aircraft, according to their accuracy and their real-time classification speed
Neural network based beamforming for linear and cylindrical array applications
Güreken, Murat; Dural Ünver, Mevlüde Gülbin; Department of Electrical and Electronics Engineering (2009)
In this thesis, a Neural Network (NN) based beamforming algorithm is proposed for real time target tracking problem. The algorithm is performed for two applications, linear and cylindrical arrays. The linear array application is implemented with equispaced omnidirectional sources. The influence of the number of antenna elements and the angular seperation between the incoming signals on the performance of the beamformer in the linear array beamformer is studied, and it is observed that the algorithm improves...
Neural networks with piecewise constant argument and impact activation
Yılmaz, Enes; Akhmet, Marat; Department of Scientific Computing (2011)
This dissertation addresses the new models in mathematical neuroscience: artificial neural networks, which have many similarities with the structure of human brain and the functions of cells by electronic circuits. The networks have been investigated due to their extensive applications in classification of patterns, associative memories, image processing, artificial intelligence, signal processing and optimization problems. These applications depend crucially on the dynamical behaviors of the networks. In t...
Neural network based optical network restoration with multiple classes of traffic
Gokisik, D; Bilgen, Semih (2003-01-01)
Neural-network-based optical network restoration is illustrated over an example in which multiple classes of traffic are considered. Over the pre-planned primary and backup capacity, optimal routing and wavelength assignment is carried out. In case of a network failure, protection routes and optimum flow values on these protection routes are extracted from a previously trained feed-forward neural network which is distributed over the optical data communications network.
Citation Formats
A. Kumluca, “Neural network modeling of an ionospheric process: temporal and spatial forecasting of the critical frequencies,” Middle East Technical University, 1997.