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Observation problem for systems governed by Partial Differential Equations (PDE) has been a research field of its own for a long time. In this paper it is presented an observer design for a class or parabolic PDE's using sliding modes theory and bacstepping-like procedure in order to achieve exponential convergence. A Volterra-like integral transformation is used to change the coordinates of the error...
The most important fact for differential neural networks dynamics is related to its weights time evolution. This is a consequence for the higher nonlinear structure describing the matrix differential equations, which are associated with the adaptive capability for this kind of neural networks. However, as we know, there is no any analytical demonstration of the weights stability. In fact, this is...
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