Entropy, Search, Complexity [electronic resource] /edited by Imre Csiszár, Gyula O. H. Katona, Gábor Tardos, Gábor Wiener.
by Csiszár, Imre [editor.]; Katona, Gyula O. H [editor.]; Tardos, Gábor [editor.]; Wiener, Gábor [editor.]; SpringerLink (Online service).
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Item type | Current location | Call number | Status | Date due | Barcode |
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MAIN LIBRARY | QA164-167.2 (Browse shelf) | Available |
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Q334-342 VOCUS: A Visual Attention System for Object Detection and Goal-Directed Search | QC174.45-174.52 Quarks and Leptons From Orbifolded Superstring | TK5105.5-5105.9 Architecture of Computing Systems - ARCS 2006 | QA164-167.2 Entropy, Search, Complexity | Q334-342 Modeling Decisions for Artificial Intelligence | RD1-811 EAES Guidelines for Endoscopic Surgery | HF54.5-54.56 Handbook on Quality and Standardisation in E-Learning |
Two Colors and More -- Coding with Feedback and Searching with Lies -- Nonadaptive and Trivial Two-Stage Group Testing with Error-Correcting d e-Disjunct Inclusion Matrices -- Model Identification Using Search Linear Models and Search Designs -- Information Topologies with Applications -- Reinforced Random Walk -- Quantum Source Coding and Data Compression -- Information Theory at the Service of Science -- Analysis of Sorting Algorithms by Kolmogorov Complexity (A Survey) -- Recognition Problems in Combinatorial Search.
The present volume is a collection of survey papers in the fields of entropy, search and complexity. They summarize the latest developments in their respective areas. More than half of the papers belong to search theory which lies on the borderline of mathematics and computer science, information theory and combinatorics, respectively. Search theory has variegated applications, among others in bioinformatics. Some of these papers also have links to linear statistics and communicational complexity. Further works survey the fundamentals of information theory and quantum source coding. The volume is recommended to experienced researchers as well as young scientists and students both in mathematics and computer science.
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