Gerontitis Dimitrios (Phd Candidate)

Thesis title: Study of Time Invariant and Varying Systems Using Recurrent Neural Networks

Supervisor: Tzekis Panagiotis

Advisory Committee Members:

Efstathios Antoniou, Professor IHU
Nicholaos Karampetakis, Professor AUTH

Abstract:

The scope of the PhD Thesis is to develop faster families of recurrent neural networks to accelerate the speed of convergence time over previous models. To be precise, we will optimize the existing functions in order to achieve faster convergence speed in finite time, to solve time varying and invariant problems such as, computation inverse of a matrix, solution of important matrix equations such as: Sylvester, Lyapunov, finding generalized inverse, solving tensor equations via Einstein product, solving non-linear equations and etc. The results and conclusions which will emerge from this PhD Thesis are expected to be particularly useful in applications, which are found in areas, such as: Robotics, Image Processing and Optimization Problems. Computer code will be developed in the Matlab’s environment to validate results and simulate specific applications.