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Books on the topic 'Network Lattice'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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1

Digitale Signalverarbeitung mit MATLAB-Praktikum: Zustandsraumdarstellung, Lattice-Strukturen, PrÞ̧diktion und adaptive Filter. Wiesbaden: Friedr. Vieweg & Sohn Verlag, 2008.

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2

Lin, Shu. Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Boston, MA: Springer US, 1998.

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3

ZnO bao mo zhi bei ji qi guang, dian xing neng yan jiu. Shanghai Shi: Shanghai da xue chu ban she, 2010.

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4

Blue Lattice Network and Other Stories. Lulu Press, Inc., 2017.

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5

Vernizzi, Graziano, and Henri Orland. Complex networks. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.43.

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This article deals with complex networks, and in particular small world and scale free networks. Various networks exhibit the small world phenomenon, including social networks and gene expression networks. The local ordering property of small world networks is typically associated with regular networks such as a 2D square lattice. The small world phenomenon can be observed in most scale free networks, but few small world networks are scale free. The article first provides a brief background on small world networks and two models of scale free graphs before describing the replica method and how it can be applied to calculate the spectral densities of the adjacency matrix and Laplacian matrix of a scale free network. It then shows how the effective medium approximation can be used to treat networks with finite mean degree and concludes with a discussion of the local properties of random matrices associated with complex networks.
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6

Zamir, Ram, Ilai Bistritz, Yuval Kochman, and Bobak Nazer. Lattice Coding for Signals and Networks. Cambridge University Press, 2014.

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7

Collet, Bernard, Andrzej Nowakowski, Thomas Michelitsch, Alejandro Perez Riascos, and Franck Nicolleau. Fractional Dynamics on Networks and Lattices. Wiley & Sons, Incorporated, John, 2019.

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8

Collet, Bernard, Andrzej Nowakowski, Thomas Michelitsch, Alejandro Perez Riascos, and Franck Nicolleau. Fractional Dynamics on Networks and Lattices. Wiley & Sons, Incorporated, John, 2019.

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9

Collet, Bernard, Andrzej Nowakowski, Thomas Michelitsch, Alejandro Perez Riascos, and Franck Nicolleau. Fractional Dynamics on Networks and Lattices. Wiley & Sons, Incorporated, John, 2019.

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10

Collet, Bernard, Andrzej Nowakowski, Thomas Michelitsch, Alejandro Perez Riascos, and Franck Nicolleau. Fractional Dynamics on Networks and Lattices. Wiley & Sons, Incorporated, John, 2019.

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11

Li, Jing, and Xiao-Ying Huang. Nanostructured crystals: An unprecedented class of hybrid semiconductors exhibiting structure-induced quantum confinement effect and systematically tunable properties. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533053.013.16.

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This article describes the structure-induced quantum confinement effect in nanostructured crystals, a unique class of hybrid semiconductors that incorporate organic and inorganic components into a single-crystal lattice via covalent (coordinative) bonds to form extended one-, two- and three-dimensional network structures. These structures are comprised of subnanometer-sized II-VI semiconductor segments (inorganic component) and amine molecules (organic component) arranged into perfectly ordered arrays. The article first provides an overview of II-VI and III-V semiconductors, II-VI colloidal quantum dots, inorganic-organic hybrid materials before discussing the design and synthesis of I-VI-based inorganic-organic hybrid nanostructures. It also considers the crystal structures, quantum confinement effect, bandgaps, and optical properties, thermal properties, thermal expansion behavior of nanostructured crystals.
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12

Kuznetsov, Sergei O., Rokia Missaoui, and Sergei Obiedkov. Formal Concept Analysis of Social Networks. Springer, 2018.

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13

Kuznetsov, Sergei O., Rokia Missaoui, and Sergei Obiedkov. Formal Concept Analysis of Social Networks. Springer, 2017.

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14

Zamir, Ram. Lattice Coding for Signals and Networks: A Structured Coding Approach to Quantization, Modulation and Multiuser Information Theory. Cambridge University Press, 2014.

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15

Zamir, Ram. Lattice Coding for Signals and Networks: A Structured Coding Approach to Quantization, Modulation, and Multiuser Information Theory. Cambridge University Press, 2014.

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16

Zamir, Ram, Ilai Bistritz, Yuval Kochman, and Bobak Nazer. Lattice Coding for Signals and Networks: A Structured Coding Approach to Quantization, Modulation, and Multiuser Information Theory. Cambridge University Press, 2014.

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17

Zamir, Ram, Ilai Bistritz, Yuval Kochman, and Bobak Nazer. Lattice Coding for Signals and Networks: A Structured Coding Approach to Quantization, Modulation, and Multiuser Information Theory. Cambridge University Press, 2014.

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18

Introduction to Lattice Algebra: With Applications in AI, Pattern Recognition, Image Analysis, and Biomimetic Neural Networks. Taylor & Francis Group, 2021.

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19

Ritter, Gerhard X., and Gonzalo Urcid. Introduction to Lattice Algebra: With Applications in AI, Pattern Recognition, Image Analysis, and Biomimetic Neural Networks. Taylor & Francis Group, 2021.

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20

Ritter, Gerhard X., and Gonzalo Urcid. Introduction to Lattice Algebra: With Applications in AI, Pattern Recognition, Image Analysis, and Biomimetic Neural Networks. Taylor & Francis Group, 2021.

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21

Holland, John H. 2. Complex physical systems (CPS). Oxford University Press, 2014. http://dx.doi.org/10.1093/actrade/9780199662548.003.0002.

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‘Complex physical systems’ considers the characteristics of complex physical systems (CPS), which are often geometric (specifically, lattice-like) arrays of elements, in which interactions typically depend only on effects propagated from nearest neighbors. The elements of a CPS follow fixed physical laws, usually expressed by differential equations—Newton’s laws of gravity and Maxwell’s laws of electromagnetism are cases in point. Neither the laws nor the elements change over time; only the positions of the elements change. CPS show several properties: self-organized criticality, self-similarity, scaling, and power laws. Examples of these properties—such as, snowflake curves, fractals, networks, dynamics, and symmetry-breaking—are discussed.
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22

(Editor), Bernhard Ganter, Gerd Stumme (Editor), and Rudolf Wille (Editor), eds. Formal Concept Analysis: Foundations and Applications (Lecture Notes in Computer Science). Springer, 2005.

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23

Pavicic, Mladen. Quantum Computation and Quantum Communication: Theory and Experiments. Springer, 2014.

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24

Quantum Computation and Quantum Communication:: Theory and Experiments. Springer, 2005.

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25

Pavicic, Mladen. Quantum Computation and Quantum Communication : : Theory and Experiments. Springer London, Limited, 2007.

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