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This volume is a collection of more than 7000 full titles of books and papers related to chaotic behaviour in nonlinear dynamics. Emphasis has been made on recent publications, but many publications which appeared before 1980 are also included. Many titles have been checked with the authors. The scope of the Bibliography is not restricted to physics and mathematics of chaos only. Applications of chaotic dynamics to other branches of natural and social sciences are also considered. Works related to chaotic dynamics, e.g., papers on turbulence dynamical systems theory and fractal geometry, are listed at the discretion of the author or the compiler. This Bibliography is expected to be an important reference book for libraries and individual researchers.
Control and Dynamic Systems: Advances in Theory in Applications, Volume 31: Advances in Aerospace Systems Dynamics and Control Systems, Part 1 of 3 deals with significant advances in technologies which support the development of aerospace systems. It also presents several algorithms and computational techniques used in complex aerospace systems. The techniques discussed in this volume include: moving-bank multiple model adaptive estimation, algorithms for multitarget sensor tracking systems; algorithms in differential dynamic programming; optimal control of linear stochastic systems; and normalized predictive deconvulation. This book is an important reference for practitioners in the field who want a comprehensive source of techniques with significant applied implications.
The finite element, an approximation method for solving differential equations of mathematical physics, is a highly effective technique in the analysis and design, or synthesis, of structural dynamic systems. Starting from the system differential equations and its boundary conditions, what is referred to as a weak form of the problem (elaborated in the text) is developed in a variational sense. This variational statement is used to define elemental properties that may be written as matrices and vectors as well as to identify primary and secondary boundaries and all possible boundary conditions. Specific equilibrium problems are also solved. This book clearly reveals the effectiveness and great significance of the finite element method available and the essential role it will play in the future as further development occurs.
This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known approaches to the identification of Wiener and Hammerstein systems which are applicable to both neural network and polynomial models. The book gives a comparative study of their gradient approximation accuracy, computational complexity, and convergence rates and furthermore presents some new and original methods concerning the model parameter adjusting with gradient-based techniques. "Identification of Nonlinear Systems Using Neural Networks and Polynomal Models" is useful for researchers, engineers and graduate students in nonlinear systems and neural network theory.