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hardcover. Zustand: Gut. 384 Seiten; 9783527325856.3 Gewicht in Gramm: 1.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 180 | Sprache: Englisch | Produktart: Bücher.

Hardcover. Zustand: Very Good. 1st Edition. Hardcover, xiv+293pp, NOT ex-library. Clean and bright throughout, unmarked text, no inscriptions, no stamps, firmly bound. A minor crease to the lower outer corner of last pages. Short creases to board corners. Issued without a dust jacket. -- A well-balanced overview of mathematical approaches to complex systems ranging from applications in chemistry and ecology to basic research questions on network complexity. Well-known pioneers in the field have edited this volume with a view to balancing classical and modern approaches to ensure broad coverage of contemporary research problems. It is a valuable addition to the literature and a must-have for anyone dealing with network complexity and complexity issues. -- Contents: 1 Functional Complexity Based on Topology [Measure for the Functional Complexity of Networks; Applications] 2 Connections Between Artificial Intelligence & Computational Complexity & Complexity of Graphs [Representation & Searching Methods; Turing Machines; Fuzzy Logic & Graphs; Fuzzy Optimization & Systems; Problems Related to AI; Topology of Complex Networks; Hierarchies; Graph Entropy; Kolmogorov Complexity] 3 Selection-Based Estimates of Complexity Unravel Some Mechanisms & Selective Pressures Underlying the Evolution of Complexity in Artificial Networks [Complexity & Evolution; Macroscopic Quantification of Organismal Complexity; Selection-Based Methods of Complexity; Informational Complexity; Fisher Geometric Model; Cost of Complexity; Quantifying Phenotypic Complexity; Darwinian Adaptive Neural Networks DANN; Different Facets of Complexity; Mechanistic Understanding of Phenotypic Complexity; Selective Pressures Acting on Phenotypic Complexity] 4 Three Types of Network Complexity Pyramid [First Type: Life's Complexity Pyramid LCP; Second Type: Network Model Complexity Pyramid; Third Type: Generalized Farey Organized Network Pyramid] 5 Computational Complexity of Graphs [Star Complexity of Graphs; From Graphs to Boolean Functions; Formula Complexity of Graphs; Lower Bounds via Graph Entropy; Depth-2 & Depth-3 Complexity; Network Complexity of Graphs] 6 Linear Complexity of a Graph [Rationale & Approach; Background; Exploration of Irreducible Graphs; Bounds on the Linear Complexity of Graphs; Some Families of Graphs; Bounds for Graphs in General] 7 Kirchhoff's Matrix-Tree Theorem Revisited: Counting Spanning Trees with the Quantum Relative Entropy [Main Result; Bounds] 8 Dimension Measure for Complex Networks [Volume Dimension; Complex Network Zeta Function & Relation to Kolmogorov Complexity; Comparison with Complexity Classes; Node-Based Definition; Linguistic-Analysis Application; Statistical Mechanics Application; Function Values; Other Work on Complexity Measures] 9 Information-Based Complexity of Networks [History & Concept of Information-Based Complexity; Mutual Information; Graph Theory & Graph Theoretic Measures: Cyclomatic Number, Spanning Trees; Erdos-Renyi Random Graphs, Small World Networks, Scale-free Networks; Graph Entropy; Information-Based Complexity of Unweighted, Unlabeled & Undirected Networks; Motif Expansion; Labeled Networks; Weighted Networks; Empirical Results of Real Network Data & Artificially Generated Networks; Extension to Processes on Networks; Transfer Entropy; Medium Articulation] 10 Thermodynamic Depth in Undirected & Directed Networks [Polytopal vs Heat Flow Complexity; Characterization of Polytopal & Flow Complexity; Laplacian of a Directed Graph; Directed Heat Kernels & Heat Flow; Heat Flow-Thermodynamic Depth Complexity; Experimental Results] 11 Circumscribed Complexity in Ecological Networks [New Metaphor; Entropy as a Descriptor of Structure; Addressing Both Topology & Magnitude; Amalgamating Topology with Magnitudes; Effective Network Attributes; Limits to Complexity; Example Ecosystem Network; New Window on Complex Dynamics] 12 Metros as Biological Systems: Complexity in Small Real-life Networks [Methodology; Interpreting Complexity; Network Centrality]; Index.

Hardcover. Zustand: Good.

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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 412 | Sprache: Englisch | Produktart: Bücher.

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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 180 | Sprache: Englisch | Produktart: Bücher.

Original-Pappband. Zustand: gut erhalten. gr8 Original-Pappband en Biologie, Chemie, Medizin (Quantitative and Network Biology. Vol. 7); XVII pp., 343 pp.

Hardcover. Zustand: Fine. Quantitative And Network Biology; 9.6 X 6.8 X 0.8 inches; 308 pages; Shrink wrapped. Like New.; - We're committed to your satisfaction. We offer free returns and respond promptly to all inquiries. Your item will be carefully wrapped in bubble wrap and securely boxed. All orders ship on the same or next business day. Buy with confidence.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 'Information Theory and Statistical Learning' presents theoretical and practical results about information theoretic methods used in the context of statistical learning. The book will present a comprehensive overview of the large range of different methods that have been developed in a multitude of contexts. Each chapter is written by an expert in the field. The book is intended for an interdisciplinary readership working in machine learning, applied statistics, artificial intelligence, biostatistics, computational biology, bioinformatics, web mining or related disciplines.Advance Praise for 'Information Theory and Statistical Learning':'A new epoch has arrived for information sciences to integrate various disciplines such as information theory, machine learning, statistical inference, data mining, model selection etc. I am enthusiastic about recommending the present book to researchers and students, because it summarizes most of these new emerging subjects and methods, which are otherwise scattered in many places.' Shun-ichi Amari, RIKEN Brain Science Institute, Professor-Emeritus at the University of Tokyo.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 'Information Theory and Statistical Learning' presents theoretical and practical results about information theoretic methods used in the context of statistical learning. The book will present a comprehensive overview of the large range of different methods that have been developed in a multitude of contexts. Each chapter is written by an expert in the field. The book is intended for an interdisciplinary readership working in machine learning, applied statistics, artificial intelligence, biostatistics, computational biology, bioinformatics, web mining or related disciplines.Advance Praise for 'Information Theory and Statistical Learning':'A new epoch has arrived for information sciences to integrate various disciplines such as information theory, machine learning, statistical inference, data mining, model selection etc. I am enthusiastic about recommending the present book to researchers and students, because it summarizes most of these new emerging subjects and methods, which are otherwise scattered in many places.' Shun-ichi Amari, RIKEN Brain Science Institute, Professor-Emeritus at the University of Tokyo.

hardcover. Zustand: Sehr gut. 454 Seiten; 9783527327508.2 Gewicht in Gramm: 2.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. pp. 450.

hardcover. Zustand: Gut. 480 Seiten; 9783527323456.3 Gewicht in Gramm: 2.

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