Multilayer Neural Networks A Generalized Net Perspective /

• Κύριος συγγραφέας: Krawczak, Maciej (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Heidelberg : Springer International Publishing : Imprint: Springer, 2013.
• Σειρά: Studies in Computational Intelligence, 478
• Θέματα: Engineering.; Artificial intelligence.; Computational intelligence.; Control engineering.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).; Control.

 The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, like dynamic programming, with modifications, can yield a new class of learning algorithms for multilayer neural networks. Another purpose of this book is to show that the generalized net theory can be successfully used as a new description of multilayer neural networks. Several generalized net descriptions of neural networks functioning processes are considered, namely: the simulation process of networks, a system of neural networks and the learning algorithms developed in this book. The generalized net approach to modelling of real systems may be used successfully for the description of a variety of technological and intellectual problems, it can be used not only for representing the parallel functioning of homogenous objects, but also for modelling non-homogenous systems, for example systems which consist of a different kind of subsystems. The use of the generalized nets methodology shows a new way to describe functioning of discrete dynamic systems.  . 

 Introduction to Multilayer Neural Networks -- Basics of Generalized Nets -- Simulation Process of Neural Networks -- Learning from Examples -- Learning as a Control Process -- Parameterisation of Learning -- Adjoint Neural Networks.