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Mesoscale Models
The book helps to answer the following questions: How far have the understanding and mesoscale modeling advanced in recent decades, what are the key open questions that require further research and what are the mathematical and physical requirements for a mesoscale model intended to provide either insight or a predictive engineering tool? It is addressed to young researchers including doctoral students, postdocs and early career faculty,
Contextualizing Systems Biology
This collective monograph aims at contributing to an improved understanding of the epistemic presumptions, sociocultural implications and historically backgrounds of the newly emerging and currently expanding approach of systems biology. In doing so, it offers empirically grounded, valuable and reflexive information about a paradigmatic shift in the biosciences for a wide range of scientists working in the interdisciplinary areas of systems biology, synthetic biology, molecular biology, biology, the philosophy of science, the sociology of science and scientific knowledge, science and technology studies, technology assessment and the like. The authors of this monograph share the theoretical m...
Systems and Models
A multitude of complex systems and actors pursuing their own agenda shape the dynamics of our world. Better understanding of their actions and interactions is crucial, and can be achieved by a profound knowledge of systems and their properties, and their representation in models allowing simulation of probable behavior. Drawing on his extensive research and teaching experience in modeling and simulation of a wide range of systems - from engineering to social systems and ecosystems - the author presents the fundamental concepts and approaches for understanding and modeling the complex systems shaping the dynamics of our world. The book applies state space analysis and system dynamics to deal ...
General Systems Theory
This book demonstrates the theoretical value and practical significance of systems science and its logic of thinking by presenting a rigorously developed foundation—a tool for intuitive reasoning, which is supported by both theory and empirical evidence, as well as practical applications in business decision making. Following a foundation of general systems theory, the book presents an applied method to intuitively learn system-sciences fundamentals. The third and final part examines applications of the yoyo model and the theoretical results developed earlier within the context of problems facing business decision makers by organically combining methods of traditional science, the first dimension of science, with those of systems science, the second dimension, as argued by George Klir in the 1990s. This text would benefit graduate students, researchers, or practitioners in the areas of mathematics, systems science or engineering, economics, and business decision science.
Discrete-Time and Discrete-Space Dynamical Systems
Discrete-Time and Discrete-Space Dynamical Systems provides a systematic characterization of the similarities and differences of several types of discrete-time and discrete-space dynamical systems, including: Boolean control networks; nondeterministic finite-transition systems; finite automata; labelled Petri nets; and cellular automata. The book's perspective is primarily based on topological properties though it also employs semitensor-product and graph-theoretic methods where appropriate. It presents a series of fundamental results: invertibility, observability, detectability, reversiblity, etc., with applications to systems biology. Academic researchers with backgrounds in applied mathematics, engineering or computer science and practising engineers working with discrete-time and discrete-space systems will find this book a helpful source of new understanding for this increasingly important class of systems. The basic results to be found within are of fundamental importance for further study of related problems such as automated synthesis and safety control in cyber-physical systems using formal methods.
Systems Theory in the Social Sciences
In an ever more complex and interrelated world, a better understanding of social systems and of the dynamics of their behavior is of crucial im portance. Many of the tools holding promise of potentially significant contributions to the analysis of social systems have been, or are being developed outside of the social sciences proper, mostly the loose collec tion of diverse scientific approaches called' systems science' or , systems theory' . The editors - all of whom are involved in social systems analysis - have made an attempt in this volume to pull together several aspects of systems science which appear to them to be of particular relevance to the study of social systems: Control systems...
General Dynamical Processes: A Mathematical Introduction
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator ...
Qualitative Simulation Modeling and Analysis
Recently there has been considerable interest in qualitative methods in simulation and mathematical model- ing. Qualitative Simulation Modeling and Analysis is the first book to thoroughly review fundamental concepts in the field of qualitative simulation. The book will appeal to readers in a variety of disciplines including researchers in simulation methodology, artificial intelligence and engineering. This book boldly attempts to bring together, for the first time, the qualitative techniques previously found only in hard-to-find journals dedicated to single disciplines. The book is written for scientists and engineers interested in improving their knowledge of simulation modeling. The "qualitative" nature of the book stresses concepts of invariance, uncertainty and graph-theoretic bases for modeling and analysis.
Algebraic Theory for Multivariable Linear Systems
Algebraic Theory for Multivariable Linear Systems
