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Introduction to lattice algebrawith applications in AI, pattern recognition, image analysis, and biomimetic neural networks /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to lattice algebraGerhard X. Ritter, Gonzalo Urcid.
其他題名:	with applications in AI, pattern recognition, image analysis, and biomimetic neural networks /
作者:	Ritter, G. X.
其他作者:	Urcid, Gonzalo.
出版者:	Boca Raton, FL :Chapman & Hall/CRC Press,2022.
面頁冊數:	1 online resource :ill.
標題:	Lattice theory.
電子資源:	https://www.taylorfrancis.com/books/9781003154242
ISBN:	9781003154242$q(electronic bk.)

Introduction to lattice algebrawith applications in AI, pattern recognition, image analysis, and biomimetic neural networks /
Ritter, G. X.

Introduction to lattice algebrawith applications in AI, pattern recognition, image analysis, and biomimetic neural networks /[electronic resource] :Gerhard X. Ritter, Gonzalo Urcid. - 1st ed. - Boca Raton, FL :Chapman & Hall/CRC Press,2022. - 1 online resource :ill.

Includes bibliographical references and index.

Lattice theory extends into virtually every branch of mathematics, ranging from measure theory and convex geometry to probability theory and topology. A more recent development has been the rapid escalation of employing lattice theory for various applications outside the domain of pure mathematics. These applications range from electronic communication theory and gate array devices that implement Boolean logic to articial intelligence and computer science in general. Introduction to LatticeAlgebra: With Applications in AI, Pattern Recognition, Image Analysis, and Biomimetic Neural Networks 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 articial intelligence with a focus on pattern recognition, multispectral image analysis, and biomimetic articial neural networks. The book is self-contained and - depending on the student's major - can be usedfor a senior undergraduate level or rst-year graduate level course. The book is also an ideal self-study guide for researchers and professionals in the above-mentioned disciplines. Features Filled with instructive examples and exercises to help build understanding Suitable for researchers, professionals and students, both in mathematics and computer science Every chapter consists of exercises with solution provided online at www.Routledge.com/9780367720292.

ISBN: 9781003154242$q(electronic bk.)Subjects--Topical Terms:

185633
Lattice theory.

LC Class. No.: QA76.9.L38 / R58 2021

Dewey Class. No.: 004.015113

Introduction to lattice algebrawith applications in AI, pattern recognition, image analysis, and biomimetic neural networks /
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