| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910144723003321 |
|
|
Autore |
Lowen Steven Bradley <1962-> |
|
|
Titolo |
Fractal-based point processes [[electronic resource] /] / Steven Bradley Lowen, Malvin Carl Teich |
|
|
|
|
|
|
|
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) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
|
|
Soggetti |
|
Point processes |
Fractals |
Electronic books. |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
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 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9910682567903321 |
|
|
Autore |
Amini Massih-Reza |
|
|
Titolo |
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part III / / edited by Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
|
|
Edizione |
[1st ed. 2023.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (722 pages) |
|
|
|
|
|
|
Collana |
|
Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 13715 |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
|
|
Soggetti |
|
Artificial intelligence |
Computer science - Mathematics |
Computer vision |
Computer networks |
Computers, Special purpose |
Computer engineering |
Artificial Intelligence |
Mathematics of Computing |
Computer Vision |
Computer Communication Networks |
Special Purpose and Application-Based Systems |
Computer Engineering and Networks |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Deep learning -- robust and adversarial machine learning -- generative models -- computer vision -- meta-learning, neural architecture search. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented |
|
|
|
|
|
|
|
|
|
|
in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; . Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track. |
|
|
|
|
|
| |