Introduction to Lattice Algebra: With Applications in Ai, Pattern Recognition, Image Analysis, and Biomimetic Neural Networks, Ritter, Gerhard X ; Urcid, Gonzalo
Автор: Ritter, Gerhard X. (consultant, Gainesville, Florida, Usa) Urcid, Gonzalo Название: Introduction to lattice algebra ISBN: 0367720299 ISBN-13(EAN): 9780367720292 Издательство: Taylor&Francis Рейтинг: Цена: 15310.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book lays emphasis on two subjects, the first being lattice algebra and the second the practical applications of that algebra. This textbook is intended to be used for a special topics course in artificial intelligence with focus on pattern recognition, multispectral image analysis, and biomimetic artificial neural networks.
Автор: Zamir Название: Lattice Coding for Signals and Networks ISBN: 0521766982 ISBN-13(EAN): 9780521766982 Издательство: Cambridge Academ Рейтинг: Цена: 25502.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Unifying information theory and digital communication through the language of lattice codes, this book provides a detailed overview for students, researchers and industry practitioners. It covers both classical work and the more recent results, including many advanced setups and techniques showing the advantages of lattice codes over traditional random-coding solutions.
Автор: Stephen D. Comer Название: Universal Algebra and Lattice Theory ISBN: 3540156917 ISBN-13(EAN): 9783540156918 Издательство: Springer Рейтинг: Цена: 4263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Ma Jingjing Название: Lecture Notes on Algebraic Structure of Lattice-Ordered Ring ISBN: 9814571423 ISBN-13(EAN): 9789814571425 Издательство: World Scientific Publishing Рейтинг: Цена: 10930.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Algebraic Structure of Lattice-Ordered Rings presents an introduction to the theory of lattice-ordered rings and some new developments in this area in the last 10-15 years. It aims to provide the reader with a good foundation in the subject, as well as some new research ideas and topic in the field.This book may be used as a textbook for graduate and advanced undergraduate students who have completed an abstract algebra course including general topics on group, ring, module, and field. It is also suitable for readers with some background in abstract algebra and are interested in lattice-ordered rings to use as a self-study book.The book is largely self-contained, except in a few places, and contains about 200 exercises to assist the reader to better understand the text and practice some ideas.
Автор: R.S. Freese; O.C. Garcia Название: Universal Algebra and Lattice Theory ISBN: 3540123296 ISBN-13(EAN): 9783540123293 Издательство: Springer Рейтинг: Цена: 4263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases.
Автор: Ma, Yao (michigan State University) Tang, Jiliang (michigan State University) Название: Deep learning on graphs ISBN: 1108831745 ISBN-13(EAN): 9781108831741 Издательство: Cambridge Academ Рейтинг: Цена: 7126.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This comprehensive text on the theory and techniques of graph neural networks takes students, practitioners, and researchers from the basics to the state of the art. It systematically introduces foundational topics such as filtering pooling, robustness, and scalability and then demonstrates applications in NLP, data mining, vision and healthcare.
Описание: This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms.
Автор: El Gayar Название: Artificial Neural Networks in Pattern Recognition ISBN: 3031206495 ISBN-13(EAN): 9783031206498 Издательство: Springer Рейтинг: Цена: 7927.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 10th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2022, held in Dubai, UAE, in November 2022. The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The conference presents papers on subject such as pattern recognition and machine learning based on artificial neural networks.
Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman-Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The concept of rational decision making is studied, and the theory of flexibly-bounded rationality is used to extend the theory of bounded rationality within the principle of the indivisibility of rationality. The theory of the marginalization of irrationality for decision making is also introduced to deal with satisficing within irrational conditions. The methods proposed are applied in biomedical engineering, condition monitoring and for modelling interstate conflict.
Автор: Vladimir Cherkassky; Jerome H. Friedman; Harry Wec Название: From Statistics to Neural Networks ISBN: 3642791212 ISBN-13(EAN): 9783642791215 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of the NATO Advances Study Institute From Statistics to Neural Networks, Theory and Pattern Recognition Applications, held in Les Arcs, Bourg Saint Maurice, France, June 21 - July 2, 1993
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