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Titlebook: Recurrent Sequences; Key Results, Applica Dorin Andrica,Ovidiu Bagdasar Textbook 2020 Springer Nature Switzerland AG 2020 recurrent sequenc

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发表于 2025-3-21 18:21:45 | 显示全部楼层 |阅读模式
书目名称Recurrent Sequences
副标题Key Results, Applica
编辑Dorin Andrica,Ovidiu Bagdasar
视频video
概述Appropriate for math olympiad competitors; Contains challenging problems and solutions.Teaches techniques and facts that are central to mathematics.Presents a diverse range of state-of-the-art topics
丛书名称Problem Books in Mathematics
图书封面Titlebook: Recurrent Sequences; Key Results, Applica Dorin Andrica,Ovidiu Bagdasar Textbook 2020 Springer Nature Switzerland AG 2020 recurrent sequenc
描述.This self-contained text presents state-of-the-art results on recurrent sequences and their applications in algebra, number theory, geometry of the complex plane and discrete mathematics. It is designed to appeal to a wide readership, ranging from scholars and academics, to undergraduate students, or advanced high school and college students training for competitions. The content of the book is very recent, and focuses on areas where significant research is currently taking place. Among the new approaches promoted in this book, the authors highlight the visualization of some recurrences in the complex plane, the concurrent use of algebraic, arithmetic, and trigonometric perspectives on classical number sequences, and links to many applications. It contains techniques which are fundamental in other areas of math and encourages further research on the topic. The introductory chapters only require good understanding of college algebra, complex numbers, analysis and basic combinatorics.For Chapters 3, 4 and 6 the prerequisites include number theory, linear algebra and complex analysis.  .The first part of the book presents key theoretical elements required for a good understanding of
出版日期Textbook 2020
关键词recurrent sequences; linear recurrence; geometric patterns; complex plane; integer sequences; combinatori
版次1
doihttps://doi.org/10.1007/978-3-030-51502-7
isbn_softcover978-3-030-51504-1
isbn_ebook978-3-030-51502-7Series ISSN 0941-3502 Series E-ISSN 2197-8506
issn_series 0941-3502
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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发表于 2025-3-21 23:37:56 | 显示全部楼层
Dorin Andrica,Ovidiu Bagdasarcombination of basic Hebbian learning with temporal smoothing of unit activities produced an attractor network learning rule that associated temporally proximal input patterns into basins of attraction. These two mechanisms were demonstrated in a model that took gray level images of faces as input.
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Dorin Andrica,Ovidiu Bagdasarn in the loop” 5..In Part II, we show how the presented models can be applied to build an efficient face localization and identification system. The face images are detected by scanning the scene with a retina feeding a hierarchical coarse-to-fine classifier. Detections are then identified in a smal
发表于 2025-3-22 12:46:49 | 显示全部楼层
Dorin Andrica,Ovidiu Bagdasarvoid incorporation of occluding or nearby surfaces. The initial hypercolumn representation also characterizes the first stage of object perception, but the image variation for objects at a given location in a 2D coordinate space may be too great to yield sufficient predictability directly from the o
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Dorin Andrica,Ovidiu Bagdasarsequences are examined. We provide an experimental study of one commercial off-the-shelf (COTS) and four recent open-source face recognition algorithms, including color-based linear discriminant analysis (LDA), local Gabor binary pattern histogram sequences (LGBPHSs), Gabor grid graphs, and interses
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Dorin Andrica,Ovidiu Bagdasaravigates around it, or as a face changes expression or pose. A set of simulations is presented which demonstrate how viewpoint invariant representations of faces can be developed from visua. experience by capturing the temporal relationships among the input patterns. The simulations explored the int
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