Banach Space Valued Neural Network Ordinary And Fractional Approximation And Interpolation 1st Edition George A Anastassiou by George A. Anastassiou 9783031163999, 9783031164002, 3031163990, 3031164008 instant download after payment.

This monograph is the continuation of authors earlier (i) 2011 monograph, Intelligent Systems: Approximation by Artificial Neural Networks, Springer, Intelligent Systems Reference Library, Volume 19, and (ii) 2016 monograph, Intelligent Systems II: Complete Approximation by Neural Network Operators, Studies in Computational Intelligence, Volume 608.

The innovation here is that the neural networks are Banach space valued, induced by a great variety of activation functions deriving from the arctangent, algebraic, Gudermannian and generalized symmetric sigmoid functions.

Reiterating, this book is about the generalization and modernization of approximation by neural network operators. Functions under approximation and the neural networks are Banach space valued. These are induced by a great variety of activation functions deriving from the arctangent, algebraic, Gudermannian, and generalized symmetric sigmoid functions. Ordinary, fractional, fuzzy, and stochastic approximations are exhibited at the univariate, fractional, and multivariate levels. Iterated-sequential approximations are also covered.

The book's results are expected to find applications in the many areas of applied mathematics, computer science and engineering, especially in artificial intelligence and machine learning. Other possible applications can be in applied sciences like statistics, economics, etc. Therefore, this book is suitable for researchers, graduate students, practitioners, and seminars of the above disciplines, also to be in all science and engineering libraries.