In Science of Synthesis: Cross Coupling and Heck-Type Reactions, expert authors present and discuss the best and most reliable methods currently available for the formation of new carbon-carbon and carbon-heteroatom bonds using these reactions, highlighted with representative experimental procedures. Together, the three volumes of Cross Coupling and Heck-Type Reactions provide an extensive overview of the current state of the art in this field of central importance in modern chemistry, and are an invaluable resource for the practicing synthetic organic chemist. This volume is focused on the formation of carbon-heteroatom bonds and carbon-carbon bonds of acidic C-H nucleophiles. The chapters are intended to provide the reader with a practical guide to the most efficient, reliable, and useful metal-catalyzed cross-coupling reactions that generate C-N, C-P, C-O, C-S, C-B, C-Si, C-CN, and C-F bonds, and C-C bonds adjacent to carbonyl functional groups. The most up-to-date and modern methods are included, including those that facilitate replacement of typically unreactive C-H bonds with carbon-heteroatom bonds. This volume is part of a 3-volume set: Cross Coupling and Heck-Type Reactions Workbench Edition General information about Science of Synthesis
Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm implementation, model simulation, and practical application of parameter setting. Readers will find solutions to problems in computation and recognition, particularly neural networks, natural computing, machine learning and compressed sensing. This volume offers a comprehensive and well-structured introduction to brain and nature-inspired learning, computation, and recognition. Presents an invaluable systematic introduction to brain and nature-inspired learning, computation and recognition Describes the biological mechanisms, mathematical analyses and scientific principles behind brain and nature-inspired learning, calculation and recognition Systematically analyzes neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature Discusses the theory and application of algorithms and neural networks, natural computing, machine learning and compression perception
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