Recent Advances in Nonlinear Dynamics and Synchronization
Theory and Applications
Seiten
2012
Springer Berlin (Verlag)
978-3-642-26057-5 (ISBN)
Springer Berlin (Verlag)
978-3-642-26057-5 (ISBN)
The selected contributions of this book shed light on a series of aspects related to nonlinear dynamics and synchronization with the aim of demonstrating some of their interesting applications in a series of selected disciplines.
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. 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.
Part 1: Theoretical aspects and recent trends.- Part 2: Some modeling and simulation examples.- Part 3: Applications in transportation.- Part 4: Applications in security related system concepts.- Part 5: Further application areas pattern recognition and communications engineering.
| Erscheint lt. Verlag | 14.3.2012 |
|---|---|
| Reihe/Serie | Studies in Computational Intelligence |
| Zusatzinfo | XII, 399 p. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 620 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik | |
| Schlagworte | Agents • Biologically Inspired • Cognition • Computational Intelligence • Control • Intelligence • learning • Modeling • Neural networks • Nonlinear Dynamics • pattern recognition • Simulation • Synchronization |
| ISBN-10 | 3-642-26057-8 / 3642260578 |
| ISBN-13 | 978-3-642-26057-5 / 9783642260575 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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