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Growing Adaptive Machines
The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researche...
TranscEnding the Global Power Game
Whatever happens on the visible plane has its roots in invisible dimensions; reality is more than meets the eye. This is the essence of all spiritual teachings and mystery schools, and it is the key to understanding what actually happens on the stage of the global power game. Here, in a unique compendium, you get to know what the world looks like when seen from this paranormal viewpoint. Step by step, the author unfolds stunning insights into the hidden dimensions of secret politics, money manipulations, and the ongoing transformation. The pieces are put together to reveal an exciting puzzle. Topics Include: • Ancient knowledge and new revelations • The conclusive meaning of the symbolis...
Iterative Methods for Solving Nonlinear Equations and Systems
Solving nonlinear equations in Banach spaces (real or complex nonlinear equations, nonlinear systems, and nonlinear matrix equations, among others), is a non-trivial task that involves many areas of science and technology. Usually the solution is not directly affordable and require an approach using iterative algorithms. This Special Issue focuses mainly on the design, analysis of convergence, and stability of new schemes for solving nonlinear problems and their application to practical problems. Included papers study the following topics: Methods for finding simple or multiple roots either with or without derivatives, iterative methods for approximating different generalized inverses, real ...
Nonlinear Maps and their Applications
In the field of Dynamical Systems, nonlinear iterative processes play an important role. Nonlinear mappings can be found as immediate models for many systems from different scientific areas, such as engineering, economics, biology, or can also be obtained via numerical methods permitting to solve non-linear differential equations. In both cases, the understanding of specific dynamical behaviors and phenomena is of the greatest interest for scientists. This volume contains papers that were presented at the International Workshop on Nonlinear Maps and their Applications (NOMA 2011) held in Évora, Portugal, on September 15-16, 2011. This kind of collaborative effort is of paramount importance in promoting communication among the various groups that work in dynamical systems and networks in their research theoretical studies as well as for applications. This volume is suitable for graduate students as well as researchers in the field.
Rings, Modules and Codes
This book contains the proceedings of the Fifth International Conference on Noncommutative Rings and their Applications, held from June 12–15, 2017, at the University of Artois, Lens, France. The papers are related to noncommutative rings, covering topics such as: ring theory, with both the elementwise and more structural approaches developed; module theory with popular topics such as automorphism invariance, almost injectivity, ADS, and extending modules; and coding theory, both the theoretical aspects such as the extension theorem and the more applied ones such as Construction A or Reed–Muller codes. Classical topics like enveloping skewfields, weak Hopf algebras, and tropical algebras are also presented.
Generative Adversarial Networks and Deep Learning
This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various appl...
Acoustic Interactions with Submerged Elastic Structures
"\berall's work in acoustic and electromagnetic scattering has evoked much interest, in the US as well as abroad, because of its possible practical applications, as well as the theoretical understanding. Many collaborators have been inspired by it, and have now contributed to this volume. The book is an excellent contribution to the literature of Acoustics and Wave Propagation. Professor Guran is to be congratulated for organizing and editing this volume." Prof. Hans A Bethe Noble Laureate Cornell University, 1996
