References: [1] Allen, B. & Ghavami, M. (2005). Adaptive Array Systems: Fundamentals and Applications. Wiley: Chichester. [2] Godara, L.C. & SMART (2004). Antennas. CRC Press LLC: Boca Raton. [3] Schmidt, R. (1986) Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas and Propagation, 34, 276–280. [4] Christodoulou, C.G. & Georgiopoulos, M. (2000). Application of Neural Networks in Electromagnetics. Artech House. [5] El Zooghby, A.H., Christodoulou, C.G. & Georgiopoulos, M. (2000) A neural network based smart antenna for multiple source tracking. IEEE Transactions on Antennas and Propagation, 48, 768–776. [6] Agatonovic, M., Stankovic, Z. & Doncov, N., Sit, B., Milovanovic, Application of artificial neural networks for efficient highresolution 2D DOA estimation. Radioengineering, 21, 1178–1186. [7] Stankovic, Z. & Doncov (1957) Megalocornea and cataract. Annales d’Oculistique, 190, 36–42 [PubMed: 13411747], J. Russer, I. Milovanovie, B. Milovanovie, Neural Network Approach for Efficient DOA Determination of Multiple Stochastic EM Sources in Far-field, 1st IEEE Int. Cord: on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications, NEMO 2014. [8] Stankovic, Z., Doncov, N., Milovanovic, I., Milovanovic, B. & Stoiljkovic, M. (2014) Localization of mobile users of stochastic radiation nature by using Neural Networks. Proceedings of the 49th International Scientific Conference on Information, Communication and Energy Systems and Technologies – ICEST, Ni (2014). Serbia, 25–27 June, 2014, Vol. 2, pp. 347–350. [9] Stankovic, Z., Doncov, N., Milovanovic, I. & Milovanovie, B. (2014) Neural network model for efficient localization of a number of mutually arbitrary positioned stochastic EM sources in far-field. Proceedings of the 12th Symposium on Neural Network Applications in Electrical Engineering. NEUREL: Beograd, Serbia, pp. 41–44. [10] Stankovic, Z., Doncov, N., Milovanovic, I., Sarevska, M. & Milovanovic, B. Neural model for far-field 1D localization of mobile stochastic EM sources with partially correlated radiation. Proceedings of the International Scientific. [11] Stankovie, Z., Doncov, N., Milovanovie, I. & Milovanovie, B. (2017), Ni§ ID localization of highly correlated mobile stochastic EM sources using neural model. Proceedings of the 13th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services – TELSIKI. October: Serbia 18-20, pp. 33–37. [12] Stankovic, Z., Milovanovic, I., Doncov, N. & Milovanovic, B. (2016) 2D localization of source of stochastic EM radiation by using neural networks. International Scientific Conference on Information, Communication, and Energy Systems and Technologies— ICEST. Proceedings of the Papers, p 99 -102, Vol. LI. [13] Stankovic, Z., Doncov, N., Milovanovie, B. & Milovanovic, I. (2017). Efficient 2D Localization of a Number of Mutually Arbitrary Positioned Stochastic EM Sources in Far-Field using Neural Model, accepted paper International Conference on Electromagnetics in Advanced Applications (ICEAA). Italy, September 11 — 15, 2017, ISBN: 978-1-5090-4450-4, p 1391–1394. [14] Haykin, S. (1994). Neural Networks. IEEE Publications: New York, USA. [15] Mang, Q.J. & Gupta, K.C. (2000). Neural Networks for RF and Microwave Design. Artech House: Boston, USA. [16] Russer, J.A., Asenov, T. & Russer, P. (2012). Sampling of stochastic electromagnetic fields. IEEE MTT-S International Microwave Symposium Digest, (Montreal, Canada), 1–3. [17] Russer, J.A. & Russer, P. (2015). Modeling of noisy EM field propagation using correlation information. IEEE Transactions on Microwave Theory and Techniques, 63, 76–89. |