Error Control and Adaptivity in Scientific Computing, Haydar Bulgak; Christoph Zenger

Автор: Haydar Bulgak; Christoph Zenger
Название: Error Control and Adaptivity in Scientific Computing
ISBN: 0792358082 ISBN-13(EAN): 9780792358084
Издательство: Springer
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Цена: 31305.00 р.
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Описание: One of the main ways by which we can understand complex processes is to create computerised numerical simulation models of them. This book covers topics such as error estimates and error control in numerical linear algebra algorithms (related to the concept of condition numbers), interval arithmetic and adaptivity for continuous models.

Автор: Larisa Beilina; Michael Victor Klibanov
Название: Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems
ISBN: 1489995307 ISBN-13(EAN): 9781489995308
Издательство: Springer
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Цена: 21661.00 р.
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Описание: The first of its kind, this volume presents convergent numerical methods for coefficient inverse problems for partial differential equations. Readers will find globally convergent methods that are synthesized with the Adaptive Finite Element technique (adaptivity for brevity).

Автор: Masanari Asano; Andrei Khrennikov; Masanori Ohya;
Название: Quantum Adaptivity in Biology: From Genetics to Cognition
ISBN: 9401798184 ISBN-13(EAN): 9789401798181
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book examines information processing performed by bio-systems at all scales: from genomes, cells and proteins to cognitive and even social systems. It introduces a theoretical/conceptual principle based on quantum information and non-Kolmogorov probability theory to explain information processing phenomena in biology as a whole. The book begins with an introduction followed by two chapters devoted to fundamentals, one covering classical and quantum probability, which also contains a brief introduction to quantum formalism, and another on an information approach to molecular biology, genetics and epigenetics. It then goes on to examine adaptive dynamics, including applications to biology, and non-Kolmogorov probability theory. Next, the book discusses the possibility to apply the quantum formalism to model biological evolution, especially at the cellular level: genetic and epigenetic evolutions. It also presents a model of the epigenetic cellular evolution based on the mathematical formalism of open quantum systems. The last two chapters of the book explore foundational problems of quantum mechanics and demonstrate the power of usage of positive operator valued measures (POVMs) in biological science. This book will appeal to a diverse group of readers including experts in biology, cognitive science, decision making, sociology, psychology, and physics; mathematicians working on problems of quantum probability and information and researchers in quantum foundations.