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Stochastic Dynamics
Stochastic Dynamics, born almost 100 years ago with the early explanations of Brownian motion by physicists, is nowadays a quickly expanding field of research within nonequilibrium statistical physics. The present volume provides a survey on the influence of fluctuations in nonlinear dynamics. It addresses specialists, although the intention of this book is to provide teachers and students with a reliable resource for seminar work. In particular, the reader will find many examples illustrating the theory as well as a host of recent findings.
Stochastic Climate Models
A collection of articles written by mathematicians and physicists, designed to describe the state of the art in climate models with stochastic input. Mathematicians will benefit from a survey of simple models, while physicists will encounter mathematically relevant techniques at work.
Stochastic Processes in Physics, Chemistry, and Biology
The theory of stochastic processes originally grew out of efforts to describe Brownian motion quantitatively. Today it provides a huge arsenal of methods suitable for analyzing the influence of noise on a wide range of systems. The credit for acquiring all the deep insights and powerful methods is due ma- ly to a handful of physicists and mathematicians: Einstein, Smoluchowski, Langevin, Wiener, Stratonovich, etc. Hence it is no surprise that until - cently the bulk of basic and applied stochastic research was devoted to purely mathematical and physical questions. However, in the last decade we have witnessed an enormous growth of results achieved in other sciences - especially chemistry and...
Neuro-informatics and Neural Modelling
How do sensory neurons transmit information about environmental stimuli to the central nervous system? How do networks of neurons in the CNS decode that information, thus leading to perception and consciousness? These questions are among the oldest in neuroscience. Quite recently, new approaches to exploration of these questions have arisen, often from interdisciplinary approaches combining traditional computational neuroscience with dynamical systems theory, including nonlinear dynamics and stochastic processes. In this volume in two sections a selection of contributions about these topics from a collection of well-known authors is presented. One section focuses on computational aspects from single neurons to networks with a major emphasis on the latter. The second section highlights some insights that have recently developed out of the nonlinear systems approach.
Integrative Systems Approaches to Natural and Social Dynamics
At the start of the new millennium, mankind is challenged by a paradox: the more we know about the world the more uncertain we become in understanding and predicting how it works. This book presents an outline of a new basis for Systems Science, and a methodology for its application in complex environmental, economic, social, and technological systems.
From Physics To Control Through An Emergent View
The book is a compilation of selected papers from the conference on Physics and Control 2009, presenting a unified perspective underlying the thematics and strategies related to the control of physical systems with emerging applications in physics, engineering, chemistry, biology and other natural sciences. The selected papers reflect the state-of-the-art of the more advanced theoretical and practical studies in the field of control of complex systems. The contributions provide a comprehensive view on some selected topics of particular importance at the disciplinary borderline between Physics and Control.
Stochastic Methods in Neuroscience
Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large amounts of neurophysiological data, and advances in stochastic analysis. These techniques are leading to biophysically more realistic models. It has also become clear that both neuroscientists and mathematicians profit from collaborations in this exciting research area.Graduates and researchers in computational neuroscience and stochastic systems, and neuroscientists seeking to learn more about recent advances in the modelling and analysis of noisy neural systems, will benefit from this comprehensive overview. The series of self-contain...
Dynamics
This volume of the Handbook of Surface Science covers all aspects of the dynamics of surface processes. Two dozen world leading experts in this field address the subjects of energy exchange in gas atoms, surface collisions, the rules governing dissociative adsorption on surfaces, the formation of nanostructures on surfaces by self-assembly, and the study of surface phenomena using ultra-fast lasers. The chapters are written for both newcomers to the field as well as researchers.• Covers all aspects of the dynamics of surface processes • Provides understanding of this unique field utilizing a multitude of accurate experiments and advanced microscopic theory that allows quantum-level comparisons • Presents the concepts and tools relevant beyond surface science for catalysis, nanotechnology, biology, medicine, and materials
Aspects of Mathematical Modelling
The construction of mathematical models is an essential scientific activity. Mathematics is associated with developments in science and engineering, but more recently mathematical modelling has been used to investigate complex systems that arise in other fields. This book demonstrates the application of mathematics to research topics in ecology and environmental science, health and medicine, phylogenetics and neural networks, theoretical chemistry, economics and management.
Chimera Patterns in Networks
This is the first book devoted to chimera states - peculiar partial synchronization patterns in networks. Providing an overview of the state of the art in research on this topic, it explores how these hybrid states, which are composed of spatially separated domains of synchronized and desynchronized behavior, arise surprisingly in networks of identical units and symmetric coupling topologies. The book not only describes various types of chimeras, but also discusses the role of time delay, stochasticity, and network topology for these synchronization-desynchronization patterns. Moreover, it addresses the question of robustness and control of chimera states, which have various applications in physics, biology, chemistry, and engineering. This book is intended for researchers with a background in physics, applied mathematics, or engineering. Of great interest to specialists working on related problems, it is also a valuable resource for newcomers to the field and other scientists working on the control of spatio-temporal patterns.
