References
- http://www.dt.co.kr/contents.html?article_no=2016031602109931033004
- http://news.mt.co.kr/mtview.php?no=2015022514525399240
- The Industrial Electronics Handbook 2nd Edition Intelligent systems, 2011 by Taylor and Francis Group
- Y. Iiguni ; H. Sakai ; H. Tokumaru, "A realtime learning algorithm for a multilayered neural network based on the extended Kalman filter", IEEE Transactions on Signal Processing, 40(4), Apr 1992
- E.A. Wan ; R. Van Der Merwe, "The unscented Kalman filter for nonlinear estimation", Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000. AS-SPCC. The IEEE 2000
- N. de FreitasC. AndrieuP. Hojen-SorensenM. NiranjanA. Gee. "Sequential Monte Carlo Methods for Neural Networks", Part of the Statistics for Engineering and Information Science book series (ISS), pp 359-379
- L. Vecci, .F. Piazza, and A. Uncini, "Learning and Approximation Capabilities of Adaptive Spline Activation Function Neural Networks", 11(2), Mar, 1998, pp 259-270 https://doi.org/10.1016/S0893-6080(97)00118-4
- S. Zhang, W. Chen, F. M. Ghannouchi, and Y. Chen, "An iterative pruning of 2-D digital predistortion model based on normalized polynomial terms", Microwave Symposium Digest (IMS), 2013 IEEE MTT-S International, Seattle, WA, USA
- C. K. Ing and T. L. Lai, "A stepwise regression method and consistent model selection for highdimensional sparse linear models", Institute of Statistical Science, Academia Sinica, 21(4), Oct 2011, pp1473-1513
- Z. Z. Latt and H. Wittenberg, "Improving Flood Forecasting in a Developing Country: A Comparative Study of Stepwise Multiple Linear Regression and Artificial Neural Network", Water Resources Management, 28(8) Jun 2014, pp 2109-2128
- http://www.silverwolf.co.kr/algorithm/4831
- https://en.wikipedia.org/wiki/Rectifier_(neural_networks)