Fractal-based point processes [[electronic resource] /] / Steven Bradley Lowen, Malvin Carl Teich

• Record Nr.: UNINA9910144723003321
• Autore: Lowen Steven Bradley <1962->
• Pubbl/distr/stampa: Hoboken, N.J., : Wiley-Interscience, 2005
• ISBN: 1-280-27839-0; 9786610278398; 0-470-35478-X; 0-471-75472-2; 0-471-75470-6
• Descrizione fisica: 1 online resource (628 p.)
• Collana: Wiley Series in Probability and Statistics ; ; v.366
• Altri autori (Persone): TeichMalvin Carl
• Disciplina: 514.742; 519.2/3; 519.23
• Soggetti: Point processes; Fractals; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 513-565) and index.
• Nota di contenuto: Fractal-Based Point Processes; Preface; Contents; List of Figures; List of Figures; List of Tables; List of Tables; Authors; 1 Introduction; 1.1 Fractals; 1.1 Coastline of Iceland at different scales; 1.2 Point Processes; 1.3 Fractal-Based Point Processes; 1.2 Vehicular-traffic point process; Problems; 1.1 Length of Icelandic coastline at different scales; 1.2 Polygon approximation for perimeter of circle; 2 Scaling, Fractals, and Chaos; 2.1 Dimension; 2.1 Representative objects: measurements and dimensions; 2.2 Scaling Functions; 2.3 Fractals; 2.4 Examples of Fractals; 2.1 Cantor-set construction2.2 Realization of Brownian motion; 2.3 Fern: a nonrandom natural fractal; 2.4 Grand Canyon: a random natural fractal; 2.5 Examples of Nonfractals; 2.5 Realization of a homogeneous Poisson process; 2.6 Deterministic Chaos; 2.6 Nonchaotic system with nonfractal attractor: time course; 2.7 Chaotic system with nonfractal attractor: time course; 2.8 Chaotic system with fractal attractor; 2.9 ; Chaotic system with fractal attractor: time course; 2.10 Nonchaotic system with fractal attractor; 2.7 Origins of Fractal Behavior; 2.11 Nonchaotic system with fractal attractor: time course2.8 Ubiquity of Fractal Behavior; Problems; 3 Point Processes: Definition and Measures; 3.1 Point Processes; 3.2 Representations; 3.1 Point-process representations; 3.3 Interval-Based Measures; 3.2 Rescaled-range analysis: pseudocode; 3.3 Rescaled-range analysis: illustration; 3.4 Detrended fluctuation analysis: pseudocode; 3.4 Count-Based Measures; 3.5 Detrended fluctuation analysis: illustration; 3.6 Construction of normalized variances; 3.5 Other Measures; Problems; 4 Point Processes: Examples; 4.1 Homogeneous Poisson Point Process; 4.2 Renewal Point Processes4.3 Doubly Stochastic Poisson Point Processes; 4.1 Stochastic-rate point processes; 4.4 Integrate-and-Reset Point Processes; 4.5 Cascaded Point Processes; 4.2 Cascaded point process; 4.6 Branching Point Processes; 4.7 Lévy-Dust Counterexample; Problems; 5 Fractal and Fractal-Rate Point Processes; 5.1 Measures of Fractal Behavior in Point Processes; 5.2 Ranges of Power-Law Exponents; 5.3 Relationships among Measures; 5.4 Examples of Fractal Behavior in Point Processes; 5.1 Representative rate spectra; 5.2 Representative normalized Haar-wavelet variances; 5.5 Fractal-Based Point Processes5.3 Normalized Daubechies-wavelet variances; 5.4 Fractal and nonfractal point processes; 5.5 Fractal-rate and nonfractal point processes; Problems; 5.6 Estimated normalized-variance curves; 5.7 Representative interval spectra; 5.8 Representative interval wavelet variances; 5.9 Representative interevent-interval histograms; 5.10 Representative capacity dimensions; 5.11 Generalized dimensions for an exocytic point process; 6 Processes Based on Fractional Brownian Motion; 6.1 Fractional Brownian Motion; 6.1 Realizations of fractional Brownian motion; 6.2 Fractional Gaussian Noise
• Sommario/riassunto: An integrated approach to fractals and point processesThis publication provides a complete and integrated presentation of the fields of fractals and point processes, from definitions and measures to analysis and estimation. The authors skillfully demonstrate how fractal-based point processes, established as the intersection of these two fields, are tremendously useful for representing and describing a wide variety of diverse phenomena in the physical and biological sciences. Topics range from information-packet arrivals on a computer network to action-potential occurrences in a neural