A brief insight on applications of recurrent neural networks to general optimization problems in diverse fields such as mechanical, electrical and industrial engineering, operational research, management sciences, computer sciences, system analysis, economics, medical sciences, manufacturing...
A study in the applications of direct neural control (DNC) based on back propagation neural networks (BPN) with specialized learning architecture applied to the speed control of DC servo motor.
A study to develop robust learning algorithms with variable or adaptive learning coeficients to obtain a tradeoff between the stability and fast convergence speed.
A study in the new developments and usage of Cellular Neural Networks (a parallel computing paradigm were communication is allowed only between neighboring units) for application to image processing.
An overview on general classes of nonlinear systems based on mathematical theories and Lyapunov stability theories developed for applications to a controlled plant in a class of non-affine nonlinear implicit function and smooth with consideration to the control input.