Описание: Genetic Algorithms (GA) and Artificial Neural Networks (ANN) have progressively increased in importance amongst the techniques routinely used in chemometrics. Divided into two sections (GA and ANN), this book contains contributions from experts in the field and is of use to those who are using or are interested in GA and ANN.
Автор: Parker J J Название: Algorithms for Image Processing and Computer Vision ISBN: 0470643854 ISBN-13(EAN): 9780470643853 Издательство: Wiley Рейтинг: Цена: 12514.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Programmers, scientists, and engineers are always in need of newer techniques and algorithms to manipulate and interpret images. Algorithms for Image Processing and Computer Vision is an accessible collection of algorithms for common image processing applications that simplifies complicated mathematical calculations.
Автор: Kocay William Название: Graphs, Algorithms, and Optimization ISBN: 1482251167 ISBN-13(EAN): 9781482251166 Издательство: Taylor&Francis Рейтинг: Цена: 12554.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The second edition of this popular book presents the theory of graphs from an algorithmic viewpoint. The authors present the graph theory in a rigorous, but informal style and cover most of the main areas of graph theory. The ideas of surface topology are presented from an intuitive point of view. We have also included a discussion on linear programming that emphasizes problems in graph theory. The text is suitable for students in computer science or mathematics programs.
Автор: Asmussen Название: Stochastic Simulation: Algorithms and Analysis ISBN: 038730679X ISBN-13(EAN): 9780387306797 Издательство: Springer Рейтинг: Цена: 6981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value. Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of Engineering at Stanford University.
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