1. Nouir, Z., B. Sayrac, B. Fourestie, and R. Nasri, "Enhancement of network planning tool predictions through measurements," IEEE 63rd Vehicular Technology Conference, 1117-1121, Melbourne, Vic., DOI: 10.1109/VETECS.2006.1683008, 2006.
2. Isabona, J. and V. M. Srivastava, "Hybrid neural network approach for predicting signal propagation loss in urban microcells," IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 1-5, Agra, India, DOI: 10.1109/R10-HTC.2016.7906853, 2016.
3. Ostlin, E., H. J. Zepernick, and H. Suzuki, "Macro-cell path-loss prediction using Artificial Neural Networks," IEEE Transactions on Vehicular Technology, Vol. 59, No. 6, 2735-2747, DOI:10.1109/TVT.2010.2050502, Jul. 2010.
doi:10.1109/TVT.2010.2050502
4. Han, P., X. J. Mao, S. M. Jiao, H. R. Sun, and L. H. Zhou, "Adaptive neural network control for drum water level based on fuzzy Self-Tuning," 2006 International Conference on Machine Learning and Cybernetics, 314-318, Dalian, China, 2006.
5. Andrea, N., C. Cecchetti, and A. Lipparwi, "Fast prediction of performance of wireless links by simulation trained neural networks," Proceeding of IEEE MTT-S Digest 2000, 429-432, 2000.
6. Peng, H. and S. Zhu, "Handling of incomplete data sets using ICA and SOM in data mining," Neural Computing & Applications, Vol. 16, No. 2, 167-172, DOI:10.1016/0893-6080(88)90017-2, 2007.
doi:10.1007/s00521-006-0058-6
7. Wang, S. H., "Application of self-organising maps for data mining with incomplete data sets," Neural Computing & Applications, Vol. 12, No. 1, 42-48, DOI:10.1016/S08936080(97), 2003.
doi:10.1007/s00521-003-0372-1
8. Xu, S. and L. Chen, "Adaptive higher order neural networks," 2009 WRI Global Congress on Intelligent Systems, 26-30, Xiamen, DOI:10.4018/978-1-59904-897-0.ch014, 2009.
9. Isabona, J. and V. M. Srivastava, "Hybrid neural network approach for predicting signal propagation loss in urban microcells networks," International Journal of Applied Engineering Research, Vol. 11, No. 22, 11002-11008, DOI: 10.1109/R10-HTC.2016.7906853, 2016.
10. Sotiroudis, S. P., K. Siakavara, and J. N. Sahalos, "A neural network approach to the prediction of the propagation path-loss for mobile communications systems in urban environments," PIERS Proceedings, 162-166, Prague, Czech Republic, Aug. 27-30, 2007.
11. Neskovic, A., N. Neskovic, and D. Paunovic, "Indoor electric field level prediction model based on the artificial neural networks," IEEE Communications Letters, Vol. 4, No. 6, 190-192, DOI: 10.1109/4234.848409, 2000.
doi:10.1109/4234.848409
12. Fraile, R., L. Rubio, and N. Cardona, "Application of RBF neural networks to the prediction of propagation loss over irregular terrain," Proc. IEEE 52th Vehicular Tech. Conf., Vol. 2, 878-884, DOI: 10.1109/VETECF.2000.887127, Fall 2000.
13. Fraile, R. and N. Cardona, "Fast neural network method for propagation loss prediction in urban environments," Electronics Letters, Vol. 33, No. 24, 2056-2058, DOI: 10.1049/el: 19971378, 1997.
doi:10.1049/el:19971378
14. Lee, W. H. and A. K. Y. Lai, "Function-based and physics-based hybrid modular neural network for radio wave propagation modeling," IEEE Antennas and Propagation Society International Symposium. C, 446-449, Salt Lake City, UT, USA, DOI: 10.1109/APS.2000.873858, 2000.
15. Venkata Ramana, R., B. Krishna, S. R. Kumar, and N. G. Pandey, "Monthly rainfall prediction using wavelet neural networks analysis," International Journal of Water Resources Management, Vol. 27, 3696-3711, DOI 10.1007/s11269-013-0374-4, 2013.
16. Zhang, M., S. Xu, and J. Fulcher, "Neuron-adaptive higher order neural-network models for automated financial data modelling," IEEE Transactions on Neural Networks, Vol. 13, No. 1, 188-204, DOI: 1045-9227(02)00361-2, 2002.
doi:10.1109/72.977302
17. Ramana, R. V., B. Krishna, S. R. Kumar, and N. G. Pandey, "Monthly rainfall prediction using wavelet neural network analysis," International Journal of Water Resource Management, Vol. 27, 3697-3711, DOI: 10.1007/s11269-013-0374-4, 2013.
18. Chou, C. C., "A threshold based wavelet denoising method for hydrological data modelling," International Journal of Water Resource Management, Vol. 25, 1809-1830, DOI: 10.1080/02626667.2017.1371849, 2011.
19. Adamowski, J. and K. Sun, "Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds," Journal of Hydrology, Vol. 390, No. 1-2, 85-91, DOI: 10.1016/j.jhydrol.2010.06.033, 2010.
doi:10.1016/j.jhydrol.2010.06.033
20. Wu, D., J. Wang, and Y. Teng, "Prediction of under-groundwater levels using wavelet decompositions and transforms," Journal of Hydrology Engineering, Vol. 5, 34-39, 2004.
21. Ali, A., R. Ghazali, and M. Mat Deris, "The wavelet multilayer perception for the prediction of earthquake time series data," Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services, 138-143, Ho Chi Minh City, Vietnam, DOI: 10.1145/2095536.2095561, 2011.
22. Wu, C. L., K. W. Chau, and C. Fan, "Prediction of rainfall time series using modular artificial neural networks coupled with data preprocessing techniques," Journal of Hydrology, Vol. 389, No. 1-2, 146-167, DOI:10.1016/j.jhydrol..05.040, 2010.
doi:10.1016/j.jhydrol.2010.05.040
23. Jia, X., B. De Brabandere, T. Tuytelaars, and L. V. Gool, "Dynamic filter networks," 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain, 2016.
24. Jothiprakash, V. and A. S. Kote, "Improving the performance of data-driven techniques through data pre-processing for modelling daily reservoir inflow," Journal of Hydrol. Sci. J, Vol. 56, 168-186, DOI: 10.1080/02626667.2010.546358, 2011.
25. Vijayakumar, N. N. and B. Plale, "Prediction of missing events in sensor data streams using Kalman Filters," Proceedings of the 1st Int’l Workshop on Knowledge Discovery from Sensor Data, in conjunction with ACM 13th Int’l Conference on Knowledge Discovery and Data Mining, 1-9, Aug. 2007.
26. Dotche, K. A., F. Sekyere, and W. Banuenulmah, "LPC for Signal analysis in cellular network coverage," Open Access Library Journal, Vol. 3, No. e2759, 1-10, DO1: 10.4236/oalib.1102759, 2016.
27. Chen, W. and K. Chau, "Intelligent manipulation and calibration of parameters for hydrological models," Int. Journal on. Environ. Pollut, Vol. 28, 432-447, 2006.
doi:10.1504/IJEP.2006.011221
28. Nawi, N. M., W. H. Atomi, and M. Z. Zehman, "The Effect of data preprocessing on optimized training of artificial neural Networks," Procedia Technology, Vol. 11, 32-39, 2013.
doi:10.1016/j.protcy.2013.12.159
29. Anysz, H., A. Zbiciak, and Nabi Ibadova, "The influence of input data standardization method on prediction accuracy of artificial neural networks," Procedia Engineering, Vol. 153, 66-70, DOI: 10.1016/j.proeng.2016.08.081, 2016.
30. Tripathi, V. R., "Image denoising using non-linear filter," International Journal of Modern Engineering Research (IJMER), Vol. 2, No. 6, 4543-4546, 2012.
31. Kumar, N. R. and J. U. Kumar, "A spatial mean and median filter for noise removal in digital images," International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 4, No. 1, 246-253, DOI: 10.15662/ijareeie.2015.0401037, 2015.
doi:10.15662/ijareeie.2015.0401037
32. Tukey, J. W., "Nonlinear (Nonsuperposable) methods for smoothing data," Proceedings of Congress Record EASCON, 673, Washington DC, Oct. 7-9, 1974.
33. Lukac, R., K. N. Plataniotis, and B. Smolka, "Generalized selection weighted vector filters," EURASIP Journal on Applied Signal Processing, Vol. 12, 1870-1885, 2004.
34. Ye, W. and Z. Liao, "Generalized correlativity of median filtering operator on signals," Open Journal of Discrete Mathematics, Vol. 2, 83-87, DOI: 10.4236/ojdm.2012.23015, 2015.
35. Bovik, A. C. and T. S. Huang, "A generalization of median filtering using linear combinations of order statistics," IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 31, No. 6, 1342-1349, DOI:10.1109/TASSP.1983.1164247, 1983.
doi:10.1109/TASSP.1983.1164247
36. Oten, R. and R. J. P. de Figueiredo, "An efficient method for L-filter design," IEEE Transactions on Signal Processing, Vol. 51, No. 1, 193-203, DOI: 10.1109/TSP.2002.806573, 2003.
doi:10.1109/TSP.2002.806573
37. Marquardt, D., "An algorithm for least-squares estimation of nonlinear parameters," SIAM Journal on Applied Mathematics, Vol. 11, No. 2, 431-441, DIO:10.1137/0111030, 1963.
doi:10.1137/0111030