Neural network initalization of strapdown inertial navigation systems

Özemre, Murat


Neural network based forecasting for telecommunications via ionosphere
Şenalp, Erdem Türker; Tulunay, Ersin; Tulunay, Yurdanur; Department of Electrical and Electronics Engineering (2001)
Neural network based online estimation of maneuvering steady states and control limits
Gürsoy, Gönenç; Yavrucuk, İlkay; Department of Aerospace Engineering (2010)
This thesis concerns the design and development of neural network based predictive algorithms to predict approaching aircraft limits. Therefore, approximate dynamics of flight envelope parameters such as angle of attack and load factor are constructed using neural network augmented dynamic models. Then, constructed models are used to predict steady state responses. By inverting the models and solving for critical controls at the known envelope limits, critical control inputs are calculated as well. The perf...
Neural network modeling of an ionospheric process: temporal and spatial forecasting of the critical frequencies
Kumluca, Ayça; Tulunay, Ersin; Department of Electrical and Electronics Engineering (1997)
Neural network prediction of tsunami parameters in the aegean and Marmara Seas
Erdurmaz, Muammer Sercan; Ergin, Ayşin; Department of Civil Engineering (2004)
Tsunamis are characterized as shallow water waves, with long periods and wavelengths. They occur by a sudden water volume displacement. Earthquake is one of the main reasons of a tsunami development. Historical data for an observation period of 3500 years starting from 1500 B.C. indicates that approximately 100 tsunamis occurred in the seas neighboring Turkey. Historical earthquake and tsunami data were collected and used to develop two artificial neural network models to forecast tsunami characteristics fo...
Neural network based orbit prediction for a geostationary satellite
Kutay, Ali Türker; Tulunay, Ersin; Tekinalp, Ozan (null; 2001-05-23)
An artificial Neural Network (NN) model was developed to estimate the semi-major axis (a), the eccentricity (e) and the inclination (i) of a geostationary satellite orbit. To facilitate a comparison between the NN model developed herewith and a real case, the TORKSAT lB geostationary satellite has been taken as example. A code that numerically solves the parameters of the TORKSAT's orbit, namely METUAEE1, is used to generate the training data for the NN model and to evaluate its performance. A Multi-La...
Citation Formats
M. Özemre, “Neural network initalization of strapdown inertial navigation systems,” Middle East Technical University, 2000.