Miroslav M Novak – författare

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.

Historically, science has developed by reducing complex situations to simple ones, analyzing the components and synthesizing the original situation. While this "reductionist" approach has been extremely successful, there are phenomena of such complexity that one cannot simplify them without eliminating the problem itself. Recently, attention has turned to such problems in a wide variety of fields. This is in part due to the development of fractal geometry. Fractal geometry provides the mathematical tools for handling complexity. The present volume is a collection of papers that deal with the application of fractals in both traditional scientific disciplines and in applied fields. This volume shows the advance of our understanding of complex phenomena across a spectrum of disciplines. While these diverse fields work on very different problems, fractals provide a unifying formalism for approaching these problems.

One of the ways to understand the complexity in scientific disciplines is through the use of fractal geometry. Tremendous progress has been made in this field since its inception some two decades ago. This book collects the papers at the cutting-edge, reflecting the current status of fractals. With its special emphasis on the multidisciplinary research, the book represents a unique contribution to the understanding of the complex phenomena in nature.

Every reader will find something of interest in this book — from superdiffusion of the ocean surface to fetal heartbeats, from solar wind to the wearing-out of tools, from radioactive contamination to texture analysis, from image rendering to neural developments. The all-pervading link connecting these disparate disciplines is the realization that a linear approach to the majority of natural processes is at best only an approximation that can frequently be downright misleading. Consequently, the rise of what is broadly called the theory of complexity has gained tremendous momentum in the last decade or two. This modern approach aims at, and frequently succeeds in, correctly explaining many natural processes.The papers in this volume are based on presentations of the sixth international conference exploring the above-mentioned issues. These conferences are now regular and well established among the nonlinear series of conferences. This conference series is organized in different geographical regions, to encourage international collaboration. Among the distinguishing features of the series is its multidisciplinary nature, which has been growing steadily.

This book, based on presentations made at the international conference Fractals 2002, is of interest to everyone in the general field of nonlinear dynamics. The abundance of papers from numerous disciplines makes it exciting reading and provides a unifying thread through the topics, such as ray tracing, structure of peptides, modeling fractal surfaces, cancer growth, macaque monkey cortical neurons, occurrence of earthquakes, and patterns of the World Wide Web.