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Mathematical Modeling describes a process and an object by use of the mathematical language. A process or an object is presented in a "pure form" in Mathematical Modeling when external perturbations disturbing the study are absent. Computer simulation is a natural continuation of the Mathematical Modeling. Computer simulation can be considered as a computer experiment which corresponds to an experiment in the real world. Such a treatment is rather related to numerical simulations. Symbolic simulations yield more than just an experiment. Mathematical Modeling of stochastic processes is based on the probability theory, in particular, that leads to using of random walks, Monte Carlo methods and the standard statistics tools. Symbolic simulations are usually realized in the form of solution to equations in one unknown, to a system of linear algebraic equations, both ordinary and partial differential equations (ODE and PDE). Various mathematical approaches to stability are discussed in courses of ODE and PDE.

Mathematical models.

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Reliability Modelling and Analysis in Discrete Time provides an overview of the probabilistic and statistical aspects connected with discrete reliability systems. This engaging book discusses their distributional properties and dependence structures before exploring various orderings associated between different reliability structures. Though clear explanations, multiple examples, and exhaustive coverage of the basic and advanced topics of research in this area, the work gives the reader a thorough understanding of the theory and concepts associated with discrete models and reliability structures. A comprehensive bibliography assists readers who are interested in further research and understanding. Requiring only an introductory understanding of statistics, this book offers valuable insight and coverage for students and researchers in Probability and Statistics, Electrical Engineering, and Reliability/Quality Engineering. The book also includes a comprehensive bibliography to assist readers seeking to delve deeper. Includes a valuable introduction to Reliability Theory before covering advanced topics of research and real world applications Features an emphasis on the mathematical theory of reliability modeling Provides many illustrative examples to foster reader understanding

Reliability (Engineering) --- Mathematical models.

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Fracture mechanics --- Mathematical models.

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Vibration --- Mathematical models.

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In den zentralen Modellen der Neuen Wachstumstheorie (NWT) wird durch die Einführung von Externalitäten bei der Akkumulation von Sach- und Humankapital endogenes Wachstum des Pro-Kopf-Einkommens möglich. Diese Vorgehensweise basiert auf Kenneth Arrows Konzept des learning by doing. Während dabei nachfrageseitige Aspekte des Wachstumsprozesses ausgeblendet werden, finden sich diese in den wachstumstheoretischen Arbeiten von Nicholas Kaldor. Die von ihm betonte Rolle steigender Skalenerträge und des damit verbundenen Verdoorn-Zusammenhangs bilden eine wichtige Parallele zur NWT. Anhand einer kritischen Darstellung und Gegenüberstellung beider Sichtweisen verdeutlicht der Autor die Relevanz der Beiträge Kaldors für die NWT und die Notwendigkeit einer integrierten Erklärung von Wachstumsprozessen.

Economic policy --- Mathematical models.