Táto edícia sa venuje hlbokým ponorom do aplikovanej a výpočtovej matematiky. Predstavuje najmodernejšie metódy a algoritmy, ktoré nachádzajú uplatnenie v širokej škále vedeckých disciplín. Knihy sú navrhnuté tak, aby poskytli pevný základ pre budúce generácie výskumníkov. Ide o cenný zdroj pre študentov aj profesionálov v odbore.
This book offers a comprehensive introduction to scattered data approximation theory, making it an ideal resource for graduate students and researchers. It covers essential concepts and methodologies, providing a solid foundation for understanding the subject. The text is designed to be self-contained, ensuring accessibility for those new to the field while also serving as a valuable reference for experienced practitioners.
The book offers a comprehensive guide to the numerical methods used for solving a wide range of integral equations. It covers various techniques and approaches, making it a valuable resource for those looking to understand and apply these mathematical concepts effectively.
Sure to be influential, Watanabe’s book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.