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Open Access Books » Physical Sciences, Engineering and Technology » Mathematics
Top 100 most cited* InTechOpen book titles.
* Only citations in Web of Science™ Core Collection publications are taken into consideration.

 New analytical strategies and techniques are necessary to meet requirements of modern technologies and new materials. In this sense, this book provides a thorough review of current analytical approaches, industrial practices, and strategies in Fourie ...

 This book aims to provide information about Fourier transform to those needing to use infrared spectroscopy, by explaining the fundamental aspects of the Fourier transform, and techniques for analyzing infrared data obtained for a wide number of mate ...

 Molecular Dynamics is a twovolume compendium of the evergrowing applications of molecular dynamics simulations to solve a wider range of scientific and engineering challenges. The contents illustrate the rapid progress on molecular dynamics simula ...

 Bayesian networks are a very general and powerful tool that can be used for a large number of problems involving uncertainty: reasoning, learning, planning and perception. They provide a language that supports efficient algorithms for the automatic c ...

 Nonlinearity, Bifurcation and Chaos  Theory and Application is an edited book focused on introducing both theoretical and application oriented approaches in science and engineering. It contains 12 chapters, and is recommended for u ...

 Linear algebra occupies a central place in modern mathematics. Also, it is a beautiful and mature field of mathematics, and mathematicians have developed highly effective methods for solving its problems. It is a subject well worth studying for its o ...

 Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. Because of these developments, interest in dynamic programming and Bayesian inference and their applications has greatly increased at ...

 Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various degrees of uncertainty in a mathematically sound and computationally efficient way. A Bayesian network is a graphical model that encodes probabilistic ...