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Many finite volume methods preserve further qualitative or asymptotic properties, including... Læs mere
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This book is an extended and revised version of "Numerical Semigroups with Applications," published by Springer as part of the RSME series. It starts by discussing... Læs mere
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This book approaches condensed matter physics from the perspective of quantum information science, focusing on systems with strong interaction and unconventional order for which the usual condensed matter methods like the Landau paradigm or the free fermion framework break down.
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The fifth volume of Rudolf Ahlswede’s lectures on Information Theory focuses on several problems that were at the heart of a lot of his research. After a short Part II on continuous data compression, Part III, the longest part of the book, is devoted to distributed information.
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This edited volume on data science features a variety of research ranging from theoretical to applied and computational topics.
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In closing, Part IV addresses the development of evolutionary learning algorithms with provable theoretical guarantees for several representative tasks, in which evolutionary learning offers excellent performance.
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The Power of Geometric Algebra Computing for Engineering and Quantum Computing is based on GAALOPWeb, a new user-friendly,... Læs mere
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In this book the authors aim to endow the reader with an operational, conceptual, and methodological understanding of the discrete mathematics that can be used to study, understand, and perform computing.
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Metaheuristic Algorithms in Industry 4.0 provides a guiding light to engineers, researchers, students, faculty and other professionals engaged in exploring and implementing industry 4.0 solutions in various systems and processes.
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This book provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural... Læs mere
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‘Machine Learning for Knowledge Discovery with R’ contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes most recent supervised and unsupervised machine learning methodologies