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1. |
Record Nr. |
UNINA9911137364803321 |
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Autore |
Białynicki-Birula Iwo |
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Titolo |
Modeling reality : how computers mirror life / / Iwo Białynicki-Birula, Iwona Białynicka-Birula |
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Pubbl/distr/stampa |
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Oxford ; ; New York, : Oxford University Press, 2004 |
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ISBN |
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1-4356-0969-7 |
0-19-152399-2 |
1-280-90304-X |
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Descrizione fisica |
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1 online resource (191 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Reality |
Life |
Physics - Philosophy |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references (p. [173]-175) and index. |
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Nota di contenuto |
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Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms |
13 Computers can learn: Neural networks14 Unpredictable individuals: Modeling society; 15 Universal computer: The Turing machine; 16 Hal, R2D2, and Number 5: Artificial intelligence; Epilog; Programs; Further reading; Index; A; B; C; D; E; F; G; H; I; K; L; M; N; O; P; R; S; T; U; V; W; X; Z |
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Sommario/riassunto |
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This book is for everyone (college and high-school students, school teachers and the general public) who wants to learn about many fascinating ideas that have come to the fore with recent advances in the application of computers to real life situations. Twenty five computer |
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programs greatly enhance the pleasure of learning the spellbinding topics covered in the book. - ;The book Modeling Reality covers a wide range of fascinating subjects, accessible to anyone who wants to learn about the use of computer modeling to solve a diverse range of problems, but who does not possess a specialized trai |
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2. |
Record Nr. |
UNINA9911135326303321 |
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Titolo |
Pattern recognition in soft computing paradigm / / editor Nikhil R. Pal |
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Pubbl/distr/stampa |
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Singapore ; ; New Jersey, : World Scientific, c2001 |
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ISBN |
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9786611960674 |
9781281960672 |
1281960675 |
9789812811691 |
9812811699 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (411 p.) |
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Collana |
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FLSI soft computing series ; ; 2 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Pattern recognition systems |
Pattern perception |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Contents; Series Editor's Preface; Volume Editor's Preface; Chapter 1 Dimensionality Reduction Techniques for Interactive Visualization, Exploratory Data Analysis and Classification; 1.1 Introduction; 1.2 Feature Extraction and Multivariate Data Projection; 1.3 Interactive Data Visualisation and Explorative Analysis |
1.4 Advanced Projection Methods 1.5 Conclusions and Future Work; References; Chapter 2 The Self-Organizing Map as a Tool in Knowledge Engineering; 2.1 Introduction; 2.2 Data analysis using the Self-Organizing Map; 2.3 Visualization; 2.4 Software; 2.5 Case studies |
2.6 Conclusions 2.7 Acknowledgments; References; Chapter 3 Classification of Oceanic Water Types Using Self-organizing Feature Maps; 3.1 Introduction; 3.2 Unsupervised neural networks for ocean |
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colour data processing |
3.3 Hierarchy of neural networks for the water type classification 3.4 Accomplishments of the hierarchical image processing; 3.5 Conclusions; References; Chapter 4 Feature Selection by Artificial Neural Network for Pattern Classification; 4.1 Introduction |
4.2 Fractal Neural Network Model 4.3 Feature Selection Algorithm; 4.4 Simulation and Results; 4.5 Discussion and Conclusion; References; Chapter 5 MLP Based Character Recognition using Fuzzy Features and a Genetic Algorithm for Feature Selection ; 5.1 Introduction |
5.2 Hough Transform and Multilayer Perceptron |
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Sommario/riassunto |
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Pattern recognition (PR) consists of three important tasks: feature analysis, clustering and classification. Image analysis can also be viewed as a PR task. Feature analysis is a very important step in designing any useful PR system because its effectiveness depends heavily on the set of features used to realise the system. A distinguishing feature of this volume is that it deals with all three aspects of PR, namely feature analysis, clustering and classifier design. It also encompasses image processing methodologies and image retrieval with subjective information. The other interesting aspect |
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