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This book offers a comprehensive presentation of some of the most successful and popular domain decomposition preconditioners for finite and spectral element approximations of partial differential equations. It places strong emphasis on both algorithmic and mathematical aspects. It covers in detail important methods such as FETI and balancing Neumann-Neumann methods and algorithms for spectral element methods.

This book offers a comprehensive presentation of some of the most successful and popular domain decomposition preconditioners for finite and spectral element approximations of partial differential equations. It places strong emphasis on both algorithmic and mathematical aspects. It covers in detail important methods such as FETI and balancing Neumann-Neumann methods and algorithms for spectral element methods.

Many real-world applications of pattern recognition (PR) systems require human post-processing to correct the errors committed by machines. This can create bottlenecks in recognition systems, yielding high operational costs.

This important text/reference proposes a radically different approach to this problem, in which users of a system are involved during the recognition process. This can help to avoid later errors and reduce the costs associated with post-processing. The book also examines a range of advanced multimodal interactions between the machine and the users, including...

Many real-world applications of pattern recognition (PR) systems require human post-processing to correct the errors committed by machines. This can create bottlenecks in recognition systems, yielding high operational costs.

This important text/reference proposes a radically different approach to this problem, in which users of a system are involved during the recognition process. This can help to avoid later errors and reduce the costs associated with post-processing. The book also examines a range of advanced multimodal interactions between the machine and the users, including...