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Books on the topic 'Fractal scaling'

Author: Grafiati
Published: 7 June 2025
Last updated: 26 June 2025

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1

Nottale, Laurent. Fractal space-time and microphysics: Towards a theory of scale relativity. World Scientific, 1992.

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2

Nottale, Laurent. Fractal space-time and microphysics: Towards a theory of scale relativity. World Scientific, 1993.

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3

Abry, Patrice, Paulo Gonalves, and Jacques Lvy Vhel, eds. Scaling, Fractals and Wavelets. ISTE, 2009. http://dx.doi.org/10.1002/9780470611562.

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4

Patrice, Abry, Gonçalves Paulo 1967-, and Lévy Véhel Jacques 1960-, eds. Scaling, fractals and wavelets. ISTE Ltd, 2007.

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5

Mandelbrot, Benoit B. Fractals and Scaling in Finance. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2763-0.

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6

Mandelbrot, Benoit B. Fractals and scaling in finance: Discontinuity, concentration, risk. Springer, 1997.

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7

D, Schertzer, and Lovejoy S. 1956-, eds. Non-linear variability in geophysics: Scaling and fractals. Kluwer Academic Publishers, 1991.

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8

1949-, Novak M. M., ed. Emergent nature: Patterns, growth and scaling in the sciences. World Scientific, 2001.

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9

Lovejoy, S. The weather and climate: Emergent laws and multifractal cascades. Cambridge University Press, 2012.

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10

Mandelbrot, Benoit B. Fractals and scaling in finance: Discontinuity, concentration, risk : selecta volume E. Springer, 1997.

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11

éd, Dubrulle B., Graner F. éd, Sornette D. éd, and Centre de physique des Houches., eds. Scale invariance and beyond: Les Houches Workshop, March 10-14, 1997. Springer-Verlag, 1997.

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12

Sanborn, Adrian. Scaling dimensions with fractal curves and applications to DNA folding. 2011.

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13

Fractal space-time and microphysics: Towards a theory of scale relativity. World Scientific, 1993.

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14

Boudreau, Joseph F., and Eric S. Swanson. Percolation and universality. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0008.

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Percolation deals with global properties of random configurations of local objects. While simple to implement in models, understanding percolation requires skill in pattern recognition and analysis. A cluster recognition algorithm is developed to obtain properties of percolation models. The fractal nature of a percolating system is discussed, along with general features of fractals. Scaling laws and critical exponents, which are central features of modern approaches to complex systems, are also introduced and illustrated with percolating systems. The important concept of a correlation function is also used to characterize these systems. Finally, the insensitivity of large classes of model systems with respect to short range dynamics, known as universality, is discussed in the context of percolation. This is illustrated with the modern concepts of coarse graining and the renormalization group.
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15

Fen xing cheng shi xi tong: Biao du·dui chen·kong jian fu za xing = Fractal urban systems : scaling, symmetry, spatial complexity. Ke xue chu ban she, 2008.

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16

Abry, Patrice, Paolo Goncalves, and Jacques Levy Vehel. Scaling, Fractals and Wavelets. Wiley & Sons, Incorporated, John, 2013.

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17

Abry, Patrice, Paolo Goncalves, and Jacques Levy Vehel. Scaling, Fractals and Wavelets. Wiley & Sons, Incorporated, John, 2010.

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18

Abry, Patrice, Paolo Goncalves, and Jacques Levy Vehel. Scaling, Fractals and Wavelets. Wiley & Sons, Incorporated, John, 2013.

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19

Scaling, Fractals and Wavelets. Wiley & Sons, Incorporated, John, 2010.

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20

The Essentials of Pattern Grading: The Projection of Cartesian Coordinates Into a Spherical Geometry of Fractal Order 2.5 Using Collinear Scaling As the Algebraic Matrix..... Clarified. Hanover Phist, 2003.

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21

Clarke, Andrew. The Metabolic Theory of Ecology. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199551668.003.0012.

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The model of West, Brown & Enquist (WBE) is built on the assumption that the metabolic rate of cells is determined by the architecture of the vascular network that supplies them with oxygen and nutrients. For a fractal-like network, and assuming that evolution has minimised cardiovascular costs, the WBE model predicts that s=metabolism should scale with mass with an exponent, b, of 0.75 at infinite size, and ~ 0.8 at realistic larger sizes. Scaling exponents ~ 0.75 for standard or resting metabolic rate are observed widely, but far from universally, including in some invertebrates with cardiovascular systems very different from that assumed in the WBE model. Data for field metabolic rate in vertebrates typically exhibit b ~ 0.8, which matches the WBE prediction. Addition of a simple Boltzmann factor to capture the effects of body temperature on metabolic rate yields the central equation of the Metabolic Theory of Ecology (MTE). The MTE has become an important strand in ecology, and the WBE model is the most widely accepted physical explanation for the scaling of metabolic rate with body mass. Capturing the effect of temperature through a Boltzmann factor is a useful statistical description but too simple to qualify as a complete physical theory of thermal ecology.
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22

Meakin, Paul. Fractals, Scaling and Growth Far from Equilibrium. Cambridge University Press, 2011.

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23

Fractals, scaling, and growth far from equilibrium. Cambridge University Press, 1998.

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24

Vicsek, Tamas. Fluctuations and Scaling in Biology. Oxford University Press, 2001.

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25

Vicsek, Tamas. Fluctuations and Scaling in Biology. Oxford University Press, USA, 2001.

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26

Non-Linear Variability in Geophysics: Scaling and Fractals. Springer, 2012.

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27

(Editor), D. Schertzer, and S. Lovejoy (Editor), eds. Non-Linear Variability in Geophysics: Scaling and Fractals. Springer, 1990.

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28

Schertzer, D., and S. Lovejoy. Non-Linear Variability in Geophysics: Scaling and Fractals. Springer London, Limited, 2012.

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29

Schertzer, D., and S. Lovejoy. Non-Linear Variability in Geophysics: Scaling and Fractals. Springer, 2012.

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30

Scaling in soil physics, principles and applications: Proceedings of a symposium. Soil Science Society of America, 1990.

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31

Scaling Fractals and Wavelets (Digital Signal and Image Processing series). ISTE Publishing Company, 2007.

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32

Song, Myung-Sin. Mathematics of Multilevel Systems: Data, Scaling, Images, Signals, and Fractals. World Scientific Publishing Co Pte Ltd, 2023.

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33

Mandelbrot, Benoit B., H. M. Taylor, R. E. Gomory, P. H. Cootner, E. F. Fama, and W. S. Morris. Fractals and Scaling in Finance: Discontinuity, Concentration, Risk. Selecta Volume E. Springer, 2010.

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34

Mandelbrot, Benoit B., W. S. Morris, P. H. Cootner, R. E. Gomory, and E. F. Fama. Fractals and Scaling in Finance: Discontinuity, Concentration, Risk. Selecta Volume E. Springer London, Limited, 2013.

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35

Lovejoy, Shaun, and Daniel Schertzer. Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge University Press, 2013.

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36

Lovejoy, Shaun, and Daniel Schertzer. Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge University Press, 2013.

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37

Lovejoy, Shaun, and Daniel Schertzer. Weather and Climate: Emergent Laws and Multifractal Cascades. University of Cambridge ESOL Examinations, 2013.

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38

Lovejoy, Shaun, and Daniel Schertzer. The Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge University Press, 2018.

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39

Lovejoy, Shaun, and Daniel Schertzer. Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge University Press, 2013.

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40

(Editor), B. Dubrulle, F. Graner (Editor), and D. Sornette (Editor), eds. Scale Invariance and Beyond: Les Houches Workshop, March 10-14, 1997 (Centre de Physique les Houches). Springer, 1998.

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41

Dubrulle, B., F. Graner, and D. Sornette. Scale Invariance and Beyond: Les Houches Workshop, March 10-14 1997. Springer London, Limited, 2013.

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42

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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43

Mandelbrot, Benoit B. Fractales y finanzas : Una aproximación matemática a los mercados: Arriesgar, perder y ganar. Tusquets Editores S.A., 2006.

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44

Mandelbrot, Benoit B. Fractales y finanzas : Una aproximación matemática a los mercados: Arriesgar, perder y ganar. Tusquets Editores S.A., 2006.

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45

Fractals, chaos, power laws: Minutes from an infinite paradise. W.H. Freeman, 1991.

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