@article{Sokouti_Sokouti_Haghipour_2011, title={A Non-Linear System’s Response Identification using Artificial Neural Networks}, volume={113}, url={https://eejournal.ktu.lt/index.php/elt/article/view/614}, DOI={10.5755/j01.eee.113.7.614}, abstractNote={Identifying the kind of a non-linear system at the first initial times of applying different inputs can be useful n system identification;this identification will get important while the kind of the system’s response is being predicted before reaching the %2 range of finalvalue (time delay). As the Artificial neural networks provide the best approximation for non-linear system identification, so in thisarticle the simulation is presented by the means of Radial Basis Function in MATLAB. The presented neural network is successfullyable to identify the natural responses of a non-linear system in three modes: under damped, critical damped and over damped. Ill. 5, bibl.12, tabl. 1 (in English; abstracts in English and Lithuanian).<p><a href="http://dx.doi.org/10.5755/j01.eee.113.7.614">http://dx.doi.org/10.5755/j01.eee.113.7.614</a></p>}, number={7}, journal={Elektronika ir Elektrotechnika}, author={Sokouti, B. and Sokouti, M. and Haghipour, S.}, year={2011}, month={Sep.}, pages={63-66} }