In essence, the dynamics of real world systems (i.e. engineered systems, natural systems, social systesms, etc.) is nonlinear. The analysis of this nonlinear character is generally performed through both observational and modeling processes aiming at deriving appropriate models (mathematical, logical, graphical, etc.) to simulate or mimic the spatiotemporal dynamics of the given systems. The complex intrinsic nature of these systems (i.e. nonlinearity and spatiotemporal dynamics) can lead to striking dynamical behaviors such as regular or irregular, stable or unstable, periodicity or multi-periodicity, torus or chaotic dynamics. The various potential applications of the knowledge about such dynamics in technical sciences (engineering) are being intensively demonstrated by diverse ongoing research activities worldwide. However, both the modeling and the control of the nonlinear dynamics in a range of systems is still not yet well-understood (e.g. system models with time varying coefficients, immune systems, swarm intelligent systems, chaotic and fractal systems, stochastic systems, self-organized systems, etc.). This is due amongst others to the challenging task of establishing a precise and systematic fundamental or theoretical framework (e.g. methods and tools) to analyze, understand, explain and predict the nonlinear dynamical behavior of these systems, in some cases even in real-time. The full insight in systems’ nonlinear dynamic behavior is generally achieved through approaches involving analytical, numerical and/or experimental methods.
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The selected contributions of this book shed light on a series of interesting aspects related to nonlinear dynamics and synchronization with the aim of demonstrating some of their interesting applications in a series of selected disciplines. This book contains thirteenth chapters which are organized around five main parts. The first part (containing five chapters) does focus on theoretical aspects and recent trends of nonlinear dynamics and synchronization. The second part (two chapters) presents some modeling and simulation issues through concrete application examples. The third part (two chapters) is focused on the application of nonlinear dynamics and synchronization in transportation. The fourth part (two chapters) presents some applications of synchronization in security-related system concepts. The fifth part (two chapters) considers further applications areas, i.e. pattern recognition and communication engineering.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In essence, the dynamics of real world systems (i.e. engineered systems, natural systems, social systesms, etc.) is nonlinear. The analysis of this nonlinear character is generally performed through both observational and modeling processes aiming at deriving appropriate models (mathematical, logical, graphical, etc.) to simulate or mimic the spatiotemporal dynamics of the given systems. The complex intrinsic nature of these systems (i.e. nonlinearity and spatiotemporal dynamics) can lead to striking dynamical behaviors such as regular or irregular, stable or unstable, periodicity or multi-periodicity, torus or chaotic dynamics. The various potential applications of the knowledge about such dynamics in technical sciences (engineering) are being intensively demonstrated by diverse ongoing research activities worldwide. However, both the modeling and the control of the nonlinear dynamics in a range of systems is still not yet well-understood (e.g. system models with time varying coefficients, immune systems, swarm intelligent systems, chaotic and fractal systems, stochastic systems, self-organized systems, etc.). This is due amongst others to the challenging task of establishing a precise and systematic fundamental or theoretical framework (e.g. methods and tools) to analyze, understand, explain and predict the nonlinear dynamical behavior of these systems, in some cases even in real-time. The full insight in systems' nonlinear dynamic behavior is generally achieved through approaches involving analytical, numerical and/or experimental methods. Bestandsnummer des Verkäufers 9783642260575
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In essence, the dynamics of real world systems (i.e. engineered systems, natural systems, social systesms, etc.) is nonlinear. The analysis of this nonlinear character is generally performed through both observational and modeling processes aiming at deriving appropriate models (mathematical, logical, graphical, etc.) to simulate or mimic the spatiotemporal dynamics of the given systems. The complex intrinsic nature of these systems (i.e. nonlinearity and spatiotemporal dynamics) can lead to striking dynamical behaviors such as regular or irregular, stable or unstable, periodicity or multi-periodicity, torus or chaotic dynamics. The various potential applications of the knowledge about such dynamics in technical sciences (engineering) are being intensively demonstrated by diverse ongoing research activities worldwide. However, both the modeling and the control of the nonlinear dynamics in a range of systems is still not yet well-understood (e.g. system models with time varying coefficients, immune systems, swarm intelligent systems, chaotic and fractal systems, stochastic systems, self-organized systems, etc.). This is due amongst others to the challenging task of establishing a precise and systematic fundamental or theoretical framework (e.g. methods and tools) to analyze, understand, explain and predict the nonlinear dynamical behavior of these systems, in some cases even in real-time. The full insight in systems¿ nonlinear dynamic behavior is generally achieved through approaches involving analytical, numerical and/or experimental methods.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 412 pp. Englisch. Bestandsnummer des Verkäufers 9783642260575
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Paperback. Zustand: new. Paperback. In essence, the dynamics of real world systems (i.e. engineered systems, natural systems, social systesms, etc.) is nonlinear. The analysis of this nonlinear character is generally performed through both observational and modeling processes aiming at deriving appropriate models (mathematical, logical, graphical, etc.) to simulate or mimic the spatiotemporal dynamics of the given systems. The complex intrinsic nature of these systems (i.e. nonlinearity and spatiotemporal dynamics) can lead to striking dynamical behaviors such as regular or irregular, stable or unstable, periodicity or multi-periodicity, torus or chaotic dynamics. The various potential applications of the knowledge about such dynamics in technical sciences (engineering) are being intensively demonstrated by diverse ongoing research activities worldwide. However, both the modeling and the control of the nonlinear dynamics in a range of systems is still not yet well-understood (e.g. system models with time varying coefficients, immune systems, swarm intelligent systems, chaotic and fractal systems, stochastic systems, self-organized systems, etc.). This is due amongst others to the challenging task of establishing a precise and systematic fundamental or theoretical framework (e.g. methods and tools) to analyze, understand, explain and predict the nonlinear dynamical behavior of these systems, in some cases even in real-time. The full insight in systems nonlinear dynamic behavior is generally achieved through approaches involving analytical, numerical and/or experimental methods. In essence, the dynamics of real world systems (i.e. system models with time varying coefficients, immune systems, swarm intelligent systems, chaotic and fractal systems, stochastic systems, self-organized systems, etc.). Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9783642260575
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