This book aims to develop models and modeling techniques that are useful when applied to all complex systems. It adopts both analytic tools and computer simulation. The book is intended for students and researchers with a variety of backgrounds.

"Evolution of Dynamical Structures in Complex Systems" is dedicated to the founder of synergetics, Hermann Haken, on the occasion of his 65th birthday. This volume is an attempt to gather together and review the new results and de velopments achieved by researchers from various fields during the last few years. The contents bear witness to the great success in the development of general approaches to synergetic systems as well as remarkable progress in the more tra ditional fields of synergetics such as lasers and nonlinear optics, hydrodynamics, condensed matter physics, biology, and sociology. Since their inception, the concepts of synergetics and rigorous mathematical theories have been extended to other scientific disciplines such as medicine, artifi cial intelligence and synergetic computers, and psychology. Here too, these ideas have yielded new insights, raised unexpected questions and produced innovations in both theoretical and experimental projects. The conception of self-organization, the central theme of Hermann Haken' s scientific work, has stimulated epistemo logical studies that draw relations between synergetics and the German romantic "Naturphilosophie". It is fascinating to observe how these intuitive notions of self-organization, etc., have now evolved into a precise and holistic scientific comprehension of synergetic systems. We express our deep gratitude to Dr. Angela Lahee from Springer-Verlag for her valuable help during the preparation of this book. Stuttgart R. Frjedrjch March 1992 .4.. Wunder}jn Contents Part I General Approaches On the Principles of Synergetics By A. Wunderlin ...................................... 3 Elements of a Synergetics of Evolutionary Processes By W. Ebeling ......................... . . . . . . . . . . .. . . 42 .

This book focuses on a central question in the field of complex systems: Given a fluctuating (in time or space), uni- or multi-variant sequentially measured set of experimental data (even noisy data), how should one analyse non-parametrically the data, assess underlying trends, uncover characteristics of the fluctuations (including diffusion and jump contributions), and construct a stochastic evolution equation? Here, the term "non-parametrically" exemplifies that all the functions and parameters of the constructed stochastic evolution equation can be determined directly from the measured data. The book provides an overview of methods that have been developed for the analysis of fluctuating time series and of spatially disordered structures. Thanks to its feasibility and simplicity, it has been successfully applied to fluctuating time series and spatially disordered structures of complex systems studied in scientific fields such as physics, astrophysics, meteorology, earth science, engineering, finance, medicine and the neurosciences, and has led to a number of important results. The book also includes the numerical and analytical approaches to the analyses of complex time series that are most common in the physical and natural sciences. Further, it is self-contained and readily accessible to students, scientists, and researchers who are familiar with traditional methods of mathematics, such as ordinary, and partial differential equations. The codes for analysing continuous time series are available in an R package developed by the research group Turbulence, Wind energy and Stochastic (TWiSt) at the Carl von Ossietzky University of Oldenburg under the supervision of Prof. Dr. Joachim Peinke. This package makes it possible to extract the (stochastic) evolution equation underlying a set of data or measurements.

Mathematics of Complexity and Dynamical Systems is an authoritative reference to the basic tools and concepts of complexity, systems theory, and dynamical systems from the perspective of pure and applied mathematics. Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.g. the spontaneous formation of temporal, spatial or functional structures. These systems are often characterized by extreme sensitivity to initial conditions as well as emergent behavior that are not readily predictable or even completely deterministic. The more than 100 entries in this wide-ranging, single source work provide a comprehensive explication of the theory and applications of mathematical complexity, covering ergodic theory, fractals and multifractals, dynamical systems, perturbation theory, solitons, systems and control theory, and related topics. Mathematics of Complexity and Dynamical Systems is an essential reference for all those interested in mathematical complexity, from undergraduate and graduate students up through professional researchers.

This book contains review articles surveying the wide range of applications of synergetics to complex systems of physical, chemical and biological origin. Leading scientists in each of these fields describe how the mathematical tools of synergetics and the paradigm of self-organization have led to important advances in fields as diverse as laser instabilities, pattern formation in fluids, psychology and artificial life to name but a few.

The dynamics of complex systems can clarify the creation of structures in Nature. This creation is driven by the collective interaction of constitutive elements of the system. Such interactions are frequently nonlinear and are directly responsible for the lack of prediction in the evolution process. The self-organization accompanying these processes occurs all around us and is constantly being rediscovered, under the guise of a new jargon, in apparently unrelated disciplines.This volume offers unique perspectives on aspects of fractals and complexity and, through the examination of complementary techniques, provides a unifying thread in this multidisciplinary endeavor. Do nonlinear interactions play a role in the complexity management of socio-econo-political systems? Is it possible to extract the global properties of genetic regulatory networks without knowing the details of individual genes? What can one learn by transplanting the self-organization effects known in laser processes to the study of emotions? What can the change in the level of complexity tell us about the physiological state of the organism? The reader will enjoy finding the answers to these questions and many more in this book.