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Turbo coding, turbo equalisation and space-time coding for transmission over fading channels / / Lajos Hanzo, T.H. Liew, B.L. Yeap
Turbo coding, turbo equalisation and space-time coding for transmission over fading channels / / Lajos Hanzo, T.H. Liew, B.L. Yeap
Autore Hanzo Lajos <1952->
Edizione [1st ed.]
Pubbl/distr/stampa [Hoboken, New Jersey] : , : Wiley, 2002
Descrizione fisica 1 PDF (xvii, 748 pages) : illustrations
Disciplina 003/.54
Altri autori (Persone) LiewT. H (Tong Hooi)
YeapB. L (Bee Leong)
Soggetto topico Telecommunications
Electrical & Computer Engineering
Engineering & Applied Sciences
ISBN 1-280-55564-5
9786610555642
0-470-85474-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Acknowledgments -- Historical Perspective, Motivation and Outline -- I Convolutional and Block Coding -- Convolutional Channel Coding -- Block Coding -- Soft Decoding and Performance of BCH Codes -- II Turbo Convolutional and Turbo Block Coding -- Turbo Convolutional Coding -- The Super-Trellis Structure of Convolutional Turbo Codes -- Turbo BCH Coding -- Redundant Residue Number System Codes -- III Coded Modulation: TCM, TTCM, BICM, BICM-ID -- Coded Modulation Theory and Performance -- IV Space-Time Block and Space-Time Trellis Coding -- Space-time Block Codes -- Space-Time Trellis Codes -- Turbo-coded Adaptive QAM versus Space-time Trellis Coding -- V Turbo Equalisation -- Turbo-coded Partial-response Modulation -- Turbo Equalisation for Partial-response Systems -- Turbo Equalisation Performance Bound -- Comparative Study of Turbo Equalisers -- Reduced-complexity Turbo Equaliser -- Turbo Equalisation for Space-time Trellis-coded Systems -- Summary and Conclusions -- Bibliography -- Subject Index -- Author Index -- About the Authors -- Other Related Wiley and IEEE Press Books.
Record Nr. UNINA-9910831176003321
Hanzo Lajos <1952->  
[Hoboken, New Jersey] : , : Wiley, 2002
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertain inference / / Henry E. Kyburg, Jr. and Choh Man Teng [[electronic resource]]
Uncertain inference / / Henry E. Kyburg, Jr. and Choh Man Teng [[electronic resource]]
Autore Kyburg Henry Ely <1928->
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2001
Descrizione fisica 1 online resource (xii, 298 pages) : digital, PDF file(s)
Disciplina 003/.54
Soggetto topico Uncertainty (Information theory)
Probabilities
Logic, Symbolic and mathematical
ISBN 1-107-12249-X
1-280-43029-X
9786610430291
0-511-17479-9
0-511-02068-6
0-511-15484-4
0-511-30239-8
0-511-61294-X
0-511-04748-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Half-title; Title; Copyright; Contents; Preface; 1 Historical Background; 2 First Order Logic; 3 The Probability Calculus; 4 Interpretations of Probability; 5 Nonstandard Measures of Support; 6 Nonmonotonic Reasoning; 7 Theory Replacement; 8 Statistical Inference; 9 Evidential Probability; 10 Semantics; 11 Applications; 12 Scientific Inference; Names Index; Index
Record Nr. UNINA-9910450548703321
Kyburg Henry Ely <1928->  
Cambridge : , : Cambridge University Press, , 2001
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertain inference / / Henry E. Kyburg, Jr. and Choh Man Teng [[electronic resource]]
Uncertain inference / / Henry E. Kyburg, Jr. and Choh Man Teng [[electronic resource]]
Autore Kyburg Henry Ely <1928->
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2001
Descrizione fisica 1 online resource (xii, 298 pages) : digital, PDF file(s)
Disciplina 003/.54
Soggetto topico Uncertainty (Information theory)
Probabilities
Logic, Symbolic and mathematical
ISBN 1-107-12249-X
1-280-43029-X
9786610430291
0-511-17479-9
0-511-02068-6
0-511-15484-4
0-511-30239-8
0-511-61294-X
0-511-04748-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Half-title; Title; Copyright; Contents; Preface; 1 Historical Background; 2 First Order Logic; 3 The Probability Calculus; 4 Interpretations of Probability; 5 Nonstandard Measures of Support; 6 Nonmonotonic Reasoning; 7 Theory Replacement; 8 Statistical Inference; 9 Evidential Probability; 10 Semantics; 11 Applications; 12 Scientific Inference; Names Index; Index
Record Nr. UNINA-9910782905803321
Kyburg Henry Ely <1928->  
Cambridge : , : Cambridge University Press, , 2001
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertain inference / / Henry E. Kyburg, Jr. and Choh Man Teng [[electronic resource]]
Uncertain inference / / Henry E. Kyburg, Jr. and Choh Man Teng [[electronic resource]]
Autore Kyburg Henry Ely <1928->
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2001
Descrizione fisica 1 online resource (xii, 298 pages) : digital, PDF file(s)
Disciplina 003/.54
Soggetto topico Uncertainty (Information theory)
Probabilities
Logic, Symbolic and mathematical
ISBN 1-107-12249-X
1-280-43029-X
9786610430291
0-511-17479-9
0-511-02068-6
0-511-15484-4
0-511-30239-8
0-511-61294-X
0-511-04748-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Half-title; Title; Copyright; Contents; Preface; 1 Historical Background; 2 First Order Logic; 3 The Probability Calculus; 4 Interpretations of Probability; 5 Nonstandard Measures of Support; 6 Nonmonotonic Reasoning; 7 Theory Replacement; 8 Statistical Inference; 9 Evidential Probability; 10 Semantics; 11 Applications; 12 Scientific Inference; Names Index; Index
Record Nr. UNINA-9910815803403321
Kyburg Henry Ely <1928->  
Cambridge : , : Cambridge University Press, , 2001
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertainty analysis with high dimensional dependence modelling [[electronic resource] /] / Dorota Kurowicka and Roger Cooke
Uncertainty analysis with high dimensional dependence modelling [[electronic resource] /] / Dorota Kurowicka and Roger Cooke
Autore Kurowicka Dorota <1967->
Pubbl/distr/stampa Chichester, England ; ; Hoboken, NJ, : Wiley, c2006
Descrizione fisica 1 online resource (308 p.)
Disciplina 003.54
003/.54
Altri autori (Persone) CookeRoger <1942->
Collana Wiley series in probability and statistics
Soggetto topico Uncertainty (Information theory) - Mathematics
Soggetto genere / forma Electronic books.
ISBN 1-280-64995-X
9786610649952
0-470-86307-2
0-470-86308-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Uncertainty Analysis with High Dimensional Dependence Modelling; Contents; Preface; 1 Introduction; 1.1 Wags and Bogsats; 1.2 Uncertainty analysis and decision support: a recent example; 1.3 Outline of the book; 2 Assessing Uncertainty on Model Input; 2.1 Introduction; 2.2 Structured expert judgment in outline; 2.3 Assessing distributions of continuous univariate uncertain quantities; 2.4 Assessing dependencies; 2.5 Unicorn; 2.6 Unicorn projects; 3 Bivariate Dependence; 3.1 Introduction; 3.2 Measures of dependence; 3.2.1 Product moment correlation; 3.2.2 Rank correlation; 3.2.3 Kendall's tau
3.3 Partial, conditional and multiple correlations3.4 Copulae; 3.4.1 Fr ́echet copula; 3.4.2 Diagonal band copula; 3.4.3 Generalized diagonal band copula; 3.4.4 Elliptical copula; 3.4.5 Archimedean copulae; 3.4.6 Minimum information copula; 3.4.7 Comparison of copulae; 3.5 Bivariate normal distribution; 3.5.1 Basic properties; 3.6 Multivariate extensions; 3.6.1 Multivariate dependence measures; 3.6.2 Multivariate copulae; 3.6.3 Multivariate normal distribution; 3.7 Conclusions; 3.8 Unicorn projects; 3.9 Exercises; 3.10 Supplement; 4 High-dimensional Dependence Modelling; 4.1 Introduction
4.2 Joint normal transform4.3 Dependence trees; 4.3.1 Trees; 4.3.2 Dependence trees with copulae; 4.3.3 Example: Investment; 4.4 Dependence vines; 4.4.1 Vines; 4.4.2 Bivariate- and copula-vine specifications; 4.4.3 Example: Investment continued; 4.4.4 Partial correlation vines; 4.4.5 Normal vines; 4.4.6 Relationship between conditional rank and partial correlations on a regular vine; 4.5 Vines and positive definiteness; 4.5.1 Checking positive definiteness; 4.5.2 Repairing violations of positive definiteness; 4.5.3 The completion problem; 4.6 Conclusions; 4.7 Unicorn projects; 4.8 Exercises
4.9 Supplement4.9.1 Proofs; 4.9.2 Results for Section 4.4.6; 4.9.3 Example of fourvariate correlation matrices; 4.9.4 Results for Section 4.5.2; 5 Other Graphical Models; 5.1 Introduction; 5.2 Bayesian belief nets; 5.2.1 Discrete bbn's; 5.2.2 Continuous bbn's; 5.3 Independence graphs; 5.4 Model inference; 5.4.1 Inference for bbn's; 5.4.2 Inference for independence graphs; 5.4.3 Inference for vines; 5.5 Conclusions; 5.6 Unicorn projects; 5.7 Supplement; 6 Sampling Methods; 6.1 Introduction; 6.2 (Pseudo-) random sampling; 6.3 Reduced variance sampling; 6.3.1 Quasi-random sampling
6.3.2 Stratified sampling6.3.3 Latin hypercube sampling; 6.4 Sampling trees, vines and continuous bbn's; 6.4.1 Sampling a tree; 6.4.2 Sampling a regular vine; 6.4.3 Density approach to sampling regular vine; 6.4.4 Sampling a continuous bbn; 6.5 Conclusions; 6.6 Unicorn projects; 6.7 Exercise; 7 Visualization; 7.1 Introduction; 7.2 A simple problem; 7.3 Tornado graphs; 7.4 Radar graphs; 7.5 Scatter plots, matrix and overlay scatter plots; 7.6 Cobweb plots; 7.7 Cobweb plots local sensitivity: dike ring reliability; 7.8 Radar plots for importance; internal dosimetry; 7.9 Conclusions
7.10 Unicorn projects
Record Nr. UNINA-9910143550903321
Kurowicka Dorota <1967->  
Chichester, England ; ; Hoboken, NJ, : Wiley, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertainty analysis with high dimensional dependence modelling [[electronic resource] /] / Dorota Kurowicka and Roger Cooke
Uncertainty analysis with high dimensional dependence modelling [[electronic resource] /] / Dorota Kurowicka and Roger Cooke
Autore Kurowicka Dorota <1967->
Pubbl/distr/stampa Chichester, England ; ; Hoboken, NJ, : Wiley, c2006
Descrizione fisica 1 online resource (308 p.)
Disciplina 003.54
003/.54
Altri autori (Persone) CookeRoger <1942->
Collana Wiley series in probability and statistics
Soggetto topico Uncertainty (Information theory) - Mathematics
ISBN 1-280-64995-X
9786610649952
0-470-86307-2
0-470-86308-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Uncertainty Analysis with High Dimensional Dependence Modelling; Contents; Preface; 1 Introduction; 1.1 Wags and Bogsats; 1.2 Uncertainty analysis and decision support: a recent example; 1.3 Outline of the book; 2 Assessing Uncertainty on Model Input; 2.1 Introduction; 2.2 Structured expert judgment in outline; 2.3 Assessing distributions of continuous univariate uncertain quantities; 2.4 Assessing dependencies; 2.5 Unicorn; 2.6 Unicorn projects; 3 Bivariate Dependence; 3.1 Introduction; 3.2 Measures of dependence; 3.2.1 Product moment correlation; 3.2.2 Rank correlation; 3.2.3 Kendall's tau
3.3 Partial, conditional and multiple correlations3.4 Copulae; 3.4.1 Fr ́echet copula; 3.4.2 Diagonal band copula; 3.4.3 Generalized diagonal band copula; 3.4.4 Elliptical copula; 3.4.5 Archimedean copulae; 3.4.6 Minimum information copula; 3.4.7 Comparison of copulae; 3.5 Bivariate normal distribution; 3.5.1 Basic properties; 3.6 Multivariate extensions; 3.6.1 Multivariate dependence measures; 3.6.2 Multivariate copulae; 3.6.3 Multivariate normal distribution; 3.7 Conclusions; 3.8 Unicorn projects; 3.9 Exercises; 3.10 Supplement; 4 High-dimensional Dependence Modelling; 4.1 Introduction
4.2 Joint normal transform4.3 Dependence trees; 4.3.1 Trees; 4.3.2 Dependence trees with copulae; 4.3.3 Example: Investment; 4.4 Dependence vines; 4.4.1 Vines; 4.4.2 Bivariate- and copula-vine specifications; 4.4.3 Example: Investment continued; 4.4.4 Partial correlation vines; 4.4.5 Normal vines; 4.4.6 Relationship between conditional rank and partial correlations on a regular vine; 4.5 Vines and positive definiteness; 4.5.1 Checking positive definiteness; 4.5.2 Repairing violations of positive definiteness; 4.5.3 The completion problem; 4.6 Conclusions; 4.7 Unicorn projects; 4.8 Exercises
4.9 Supplement4.9.1 Proofs; 4.9.2 Results for Section 4.4.6; 4.9.3 Example of fourvariate correlation matrices; 4.9.4 Results for Section 4.5.2; 5 Other Graphical Models; 5.1 Introduction; 5.2 Bayesian belief nets; 5.2.1 Discrete bbn's; 5.2.2 Continuous bbn's; 5.3 Independence graphs; 5.4 Model inference; 5.4.1 Inference for bbn's; 5.4.2 Inference for independence graphs; 5.4.3 Inference for vines; 5.5 Conclusions; 5.6 Unicorn projects; 5.7 Supplement; 6 Sampling Methods; 6.1 Introduction; 6.2 (Pseudo-) random sampling; 6.3 Reduced variance sampling; 6.3.1 Quasi-random sampling
6.3.2 Stratified sampling6.3.3 Latin hypercube sampling; 6.4 Sampling trees, vines and continuous bbn's; 6.4.1 Sampling a tree; 6.4.2 Sampling a regular vine; 6.4.3 Density approach to sampling regular vine; 6.4.4 Sampling a continuous bbn; 6.5 Conclusions; 6.6 Unicorn projects; 6.7 Exercise; 7 Visualization; 7.1 Introduction; 7.2 A simple problem; 7.3 Tornado graphs; 7.4 Radar graphs; 7.5 Scatter plots, matrix and overlay scatter plots; 7.6 Cobweb plots; 7.7 Cobweb plots local sensitivity: dike ring reliability; 7.8 Radar plots for importance; internal dosimetry; 7.9 Conclusions
7.10 Unicorn projects
Record Nr. UNINA-9910830022903321
Kurowicka Dorota <1967->  
Chichester, England ; ; Hoboken, NJ, : Wiley, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertainty analysis with high dimensional dependence modelling [[electronic resource] /] / Dorota Kurowicka and Roger Cooke
Uncertainty analysis with high dimensional dependence modelling [[electronic resource] /] / Dorota Kurowicka and Roger Cooke
Autore Kurowicka Dorota <1967->
Pubbl/distr/stampa Chichester, England ; ; Hoboken, NJ, : Wiley, c2006
Descrizione fisica 1 online resource (308 p.)
Disciplina 003.54
003/.54
Altri autori (Persone) CookeRoger <1942->
Collana Wiley series in probability and statistics
Soggetto topico Uncertainty (Information theory) - Mathematics
ISBN 1-280-64995-X
9786610649952
0-470-86307-2
0-470-86308-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Uncertainty Analysis with High Dimensional Dependence Modelling; Contents; Preface; 1 Introduction; 1.1 Wags and Bogsats; 1.2 Uncertainty analysis and decision support: a recent example; 1.3 Outline of the book; 2 Assessing Uncertainty on Model Input; 2.1 Introduction; 2.2 Structured expert judgment in outline; 2.3 Assessing distributions of continuous univariate uncertain quantities; 2.4 Assessing dependencies; 2.5 Unicorn; 2.6 Unicorn projects; 3 Bivariate Dependence; 3.1 Introduction; 3.2 Measures of dependence; 3.2.1 Product moment correlation; 3.2.2 Rank correlation; 3.2.3 Kendall's tau
3.3 Partial, conditional and multiple correlations3.4 Copulae; 3.4.1 Fr ́echet copula; 3.4.2 Diagonal band copula; 3.4.3 Generalized diagonal band copula; 3.4.4 Elliptical copula; 3.4.5 Archimedean copulae; 3.4.6 Minimum information copula; 3.4.7 Comparison of copulae; 3.5 Bivariate normal distribution; 3.5.1 Basic properties; 3.6 Multivariate extensions; 3.6.1 Multivariate dependence measures; 3.6.2 Multivariate copulae; 3.6.3 Multivariate normal distribution; 3.7 Conclusions; 3.8 Unicorn projects; 3.9 Exercises; 3.10 Supplement; 4 High-dimensional Dependence Modelling; 4.1 Introduction
4.2 Joint normal transform4.3 Dependence trees; 4.3.1 Trees; 4.3.2 Dependence trees with copulae; 4.3.3 Example: Investment; 4.4 Dependence vines; 4.4.1 Vines; 4.4.2 Bivariate- and copula-vine specifications; 4.4.3 Example: Investment continued; 4.4.4 Partial correlation vines; 4.4.5 Normal vines; 4.4.6 Relationship between conditional rank and partial correlations on a regular vine; 4.5 Vines and positive definiteness; 4.5.1 Checking positive definiteness; 4.5.2 Repairing violations of positive definiteness; 4.5.3 The completion problem; 4.6 Conclusions; 4.7 Unicorn projects; 4.8 Exercises
4.9 Supplement4.9.1 Proofs; 4.9.2 Results for Section 4.4.6; 4.9.3 Example of fourvariate correlation matrices; 4.9.4 Results for Section 4.5.2; 5 Other Graphical Models; 5.1 Introduction; 5.2 Bayesian belief nets; 5.2.1 Discrete bbn's; 5.2.2 Continuous bbn's; 5.3 Independence graphs; 5.4 Model inference; 5.4.1 Inference for bbn's; 5.4.2 Inference for independence graphs; 5.4.3 Inference for vines; 5.5 Conclusions; 5.6 Unicorn projects; 5.7 Supplement; 6 Sampling Methods; 6.1 Introduction; 6.2 (Pseudo-) random sampling; 6.3 Reduced variance sampling; 6.3.1 Quasi-random sampling
6.3.2 Stratified sampling6.3.3 Latin hypercube sampling; 6.4 Sampling trees, vines and continuous bbn's; 6.4.1 Sampling a tree; 6.4.2 Sampling a regular vine; 6.4.3 Density approach to sampling regular vine; 6.4.4 Sampling a continuous bbn; 6.5 Conclusions; 6.6 Unicorn projects; 6.7 Exercise; 7 Visualization; 7.1 Introduction; 7.2 A simple problem; 7.3 Tornado graphs; 7.4 Radar graphs; 7.5 Scatter plots, matrix and overlay scatter plots; 7.6 Cobweb plots; 7.7 Cobweb plots local sensitivity: dike ring reliability; 7.8 Radar plots for importance; internal dosimetry; 7.9 Conclusions
7.10 Unicorn projects
Record Nr. UNINA-9910841636003321
Kurowicka Dorota <1967->  
Chichester, England ; ; Hoboken, NJ, : Wiley, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertainty and information : foundations of generalized information theory / / George J. Klir
Uncertainty and information : foundations of generalized information theory / / George J. Klir
Autore Klir George J. <1932->
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-Interscience, , c2006
Descrizione fisica 1 online resource (519 p.)
Disciplina 003.54
003/.54
Soggetto topico Uncertainty (Information theory)
Fuzzy systems
ISBN 1-280-24298-1
9786610242986
0-470-31574-1
0-471-75557-5
0-471-75556-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgments -- 1 Introduction -- 1.1. Uncertainty and Its Significance -- 1.2. Uncertainty-Based Information -- 1.3. Generalized Information Theory -- 1.4. Relevant Terminology and Notation -- 1.5. An Outline of the Book -- Notes -- Exercises -- 2 Classical Possibility-Based Uncertainty Theory -- 2.1. Possibility and Necessity Functions -- 2.2. Hartley Measure of Uncertainty for Finite Sets -- 2.2.1. Simple Derivation of the Hartley Measure -- 2.2.2. Uniqueness of the Hartley Measure -- 2.2.3. Basic Properties of the Hartley Measure -- 2.2.4. Examples -- 2.3. Hartley-Like Measure of Uncertainty for Infinite Sets -- 2.3.1. Definition -- 2.3.2. Required Properties -- 2.3.3. Examples -- Notes -- Exercises -- 3 Classical Probability-Based Uncertainty Theory -- 3.1. Probability Functions -- 3.1.1. Functions on Finite Sets -- 3.1.2. Functions on Infinite Sets -- 3.1.3. Bayes' Theorem -- 3.2. Shannon Measure of Uncertainty for Finite Sets -- 3.2.1. Simple Derivation of the Shannon Entropy -- 3.2.2. Uniqueness of the Shannon Entropy -- 3.2.3. Basic Properties of the Shannon Entropy -- 3.2.4. Examples -- 3.3. Shannon-Like Measure of Uncertainty for Infinite Sets -- Notes -- Exercises -- 4 Generalized Measures and Imprecise Probabilities -- 4.1. Monotone Measures -- 4.2. Choquet Capacities -- 4.2.1. Mbius Representation -- 4.3. Imprecise Probabilities: General Principles -- 4.3.1. Lower and Upper Probabilities -- 4.3.2. Alternating Choquet Capacities -- 4.3.3. Interaction Representation -- 4.3.4. Mbius Representation -- 4.3.5. Joint and Marginal Imprecise Probabilities -- 4.3.6. Conditional Imprecise Probabilities -- 4.3.7. Noninteraction of Imprecise Probabilities -- 4.4. Arguments for Imprecise Probabilities -- 4.5. Choquet Integral -- 4.6. Unifying Features of Imprecise Probabilities -- Notes -- Exercises -- 5 Special Theories of Imprecise Probabilities -- 5.1. An Overview -- 5.2. Graded Possibilities -- 5.2.1. Mbius Representation -- 5.2.2. Ordering of Possibility Profiles.
5.2.3. Joint and Marginal Possibilities -- 5.2.4. Conditional Possibilities -- 5.2.5. Possibilities on Infinite Sets -- 5.2.6. Some Interpretations of Graded Possibilities -- 5.3. Sugeno l-Measures -- 5.3.1. Mbius Representation -- 5.4. Belief and Plausibility Measures -- 5.4.1. Joint and Marginal Bodies of Evidence -- 5.4.2. Rules of Combination -- 5.4.3. Special Classes of Bodies of Evidence -- 5.5. Reachable Interval-Valued Probability Distributions -- 5.5.1. Joint and Marginal Interval-Valued Probability Distributions -- 5.6. Other Types of Monotone Measures -- Notes -- Exercises -- 6 Measures of Uncertainty and Information -- 6.1. General Discussion -- 6.2. Generalized Hartley Measure for Graded Possibilities -- 6.2.1. Joint and Marginal U-Uncertainties -- 6.2.2. Conditional U-Uncertainty -- 6.2.3. Axiomatic Requirements for the U-Uncertainty -- 6.2.4. U-Uncertainty for Infinite Sets -- 6.3. Generalized Hartley Measure in Dempster-Shafer Theory -- 6.3.1. Joint and Marginal Generalized Hartley Measures -- 6.3.2. Monotonicity of the Generalized Hartley Measure -- 6.3.3. Conditional Generalized Hartley Measures -- 6.4. Generalized Hartley Measure for Convex Sets of Probability Distributions -- 6.5. Generalized Shannon Measure in Dempster-Shafer Theory -- 6.6. Aggregate Uncertainty in Dempster-Shafer Theory -- 6.6.1. General Algorithm for Computing the Aggregate Uncertainty -- 6.6.2. Computing the Aggregated Uncertainty in Possibility Theory -- 6.7. Aggregate Uncertainty for Convex Sets of Probability Distributions -- 6.8. Disaggregated Total Uncertainty -- 6.9. Generalized Shannon Entropy -- 6.10. Alternative View of Disaggregated Total Uncertainty -- 6.11. Unifying Features of Uncertainty Measures -- Notes -- Exercises -- 7 Fuzzy Set Theory -- 7.1. An Overview -- 7.2. Basic Concepts of Standard Fuzzy Sets -- 7.3. Operations on Standard Fuzzy Sets -- 7.3.1. Complementation Operations -- 7.3.2. Intersection and Union Operations -- 7.3.3. Combinations of Basic Operations.
7.3.4. Other Operations -- 7.4. Fuzzy Numbers and Intervals -- 7.4.1. Standard Fuzzy Arithmetic -- 7.4.2. Constrained Fuzzy Arithmetic -- 7.5. Fuzzy Relations -- 7.5.1. Projections and Cylindric Extensions -- 7.5.2. Compositions, Joins, and Inverses -- 7.6. Fuzzy Logic -- 7.6.1. Fuzzy Propositions -- 7.6.2. Approximate Reasoning -- 7.7. Fuzzy Systems -- 7.7.1. Granulation -- 7.7.2. Types of Fuzzy Systems -- 7.7.3. Defuzzification -- 7.8. Nonstandard Fuzzy Sets -- 7.9. Constructing Fuzzy Sets and Operations -- Notes -- Exercises -- 8 Fuzzification of Uncertainty Theories -- 8.1. Aspects of Fuzzification -- 8.2. Measures of Fuzziness -- 8.3. Fuzzy-Set Interpretation of Possibility Theory -- 8.4. Probabilities of Fuzzy Events -- 8.5. Fuzzification of Reachable Interval-Valued Probability Distributions -- 8.6. Other Fuzzification Efforts -- Notes -- Exercises -- 9 Methodological Issues -- 9.1. An Overview -- 9.2. Principle of Minimum Uncertainty -- 9.2.1. Simplification Problems -- 9.2.2. Conflict-Resolution Problems -- 9.3. Principle of Maximum Uncertainty -- 9.3.1. Principle of Maximum Entropy -- 9.3.2. Principle of Maximum Nonspecificity -- 9.3.3. Principle of Maximum Uncertainty in GIT -- 9.4. Principle of Requisite Generalization -- 9.5. Principle of Uncertainty Invariance -- 9.5.1. Computationally Simple Approximations -- 9.5.2. Probability-Possibility Transformations -- 9.5.3. Approximations of Belief Functions by Necessity Functions -- 9.5.4. Transformations Between l-Measures and Possibility Measures -- 9.5.5. Approximations of Graded Possibilities by Crisp Possibilities -- Notes -- Exercises -- 10 Conclusions -- 10.1. Summary and Assessment of Results in Generalized Information Theory -- 10.2. Main Issues of Current Interest -- 10.3. Long-Term Research Areas -- 10.4. Significance of GIT -- Notes -- Appendix A Uniqueness of the U-Uncertainty -- Appendix B Uniqueness of Generalized Hartley Measure in the Dempster-Shafer Theory -- Appendix C Correctness of Algorithm 6.1.
Appendix D Proper Range of GeneralizedShannon Entropy -- Appendix E Maximum of GSa in Section 6.9 -- Appendix F Glossary of Key Concepts -- Appendix G Glossary of Symbols -- Bibliography -- Subject Index -- Name Index.
Record Nr. UNINA-9910143425103321
Klir George J. <1932->  
Hoboken, New Jersey : , : Wiley-Interscience, , c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Uncertainty and information : foundations of generalized information theory / / George J. Klir
Uncertainty and information : foundations of generalized information theory / / George J. Klir
Autore Klir George J. <1932->
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-Interscience, , c2006
Descrizione fisica 1 online resource (519 p.)
Disciplina 003.54
003/.54
Soggetto topico Uncertainty (Information theory)
Fuzzy systems
ISBN 1-280-24298-1
9786610242986
0-470-31574-1
0-471-75557-5
0-471-75556-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgments -- 1 Introduction -- 1.1. Uncertainty and Its Significance -- 1.2. Uncertainty-Based Information -- 1.3. Generalized Information Theory -- 1.4. Relevant Terminology and Notation -- 1.5. An Outline of the Book -- Notes -- Exercises -- 2 Classical Possibility-Based Uncertainty Theory -- 2.1. Possibility and Necessity Functions -- 2.2. Hartley Measure of Uncertainty for Finite Sets -- 2.2.1. Simple Derivation of the Hartley Measure -- 2.2.2. Uniqueness of the Hartley Measure -- 2.2.3. Basic Properties of the Hartley Measure -- 2.2.4. Examples -- 2.3. Hartley-Like Measure of Uncertainty for Infinite Sets -- 2.3.1. Definition -- 2.3.2. Required Properties -- 2.3.3. Examples -- Notes -- Exercises -- 3 Classical Probability-Based Uncertainty Theory -- 3.1. Probability Functions -- 3.1.1. Functions on Finite Sets -- 3.1.2. Functions on Infinite Sets -- 3.1.3. Bayes' Theorem -- 3.2. Shannon Measure of Uncertainty for Finite Sets -- 3.2.1. Simple Derivation of the Shannon Entropy -- 3.2.2. Uniqueness of the Shannon Entropy -- 3.2.3. Basic Properties of the Shannon Entropy -- 3.2.4. Examples -- 3.3. Shannon-Like Measure of Uncertainty for Infinite Sets -- Notes -- Exercises -- 4 Generalized Measures and Imprecise Probabilities -- 4.1. Monotone Measures -- 4.2. Choquet Capacities -- 4.2.1. Mbius Representation -- 4.3. Imprecise Probabilities: General Principles -- 4.3.1. Lower and Upper Probabilities -- 4.3.2. Alternating Choquet Capacities -- 4.3.3. Interaction Representation -- 4.3.4. Mbius Representation -- 4.3.5. Joint and Marginal Imprecise Probabilities -- 4.3.6. Conditional Imprecise Probabilities -- 4.3.7. Noninteraction of Imprecise Probabilities -- 4.4. Arguments for Imprecise Probabilities -- 4.5. Choquet Integral -- 4.6. Unifying Features of Imprecise Probabilities -- Notes -- Exercises -- 5 Special Theories of Imprecise Probabilities -- 5.1. An Overview -- 5.2. Graded Possibilities -- 5.2.1. Mbius Representation -- 5.2.2. Ordering of Possibility Profiles.
5.2.3. Joint and Marginal Possibilities -- 5.2.4. Conditional Possibilities -- 5.2.5. Possibilities on Infinite Sets -- 5.2.6. Some Interpretations of Graded Possibilities -- 5.3. Sugeno l-Measures -- 5.3.1. Mbius Representation -- 5.4. Belief and Plausibility Measures -- 5.4.1. Joint and Marginal Bodies of Evidence -- 5.4.2. Rules of Combination -- 5.4.3. Special Classes of Bodies of Evidence -- 5.5. Reachable Interval-Valued Probability Distributions -- 5.5.1. Joint and Marginal Interval-Valued Probability Distributions -- 5.6. Other Types of Monotone Measures -- Notes -- Exercises -- 6 Measures of Uncertainty and Information -- 6.1. General Discussion -- 6.2. Generalized Hartley Measure for Graded Possibilities -- 6.2.1. Joint and Marginal U-Uncertainties -- 6.2.2. Conditional U-Uncertainty -- 6.2.3. Axiomatic Requirements for the U-Uncertainty -- 6.2.4. U-Uncertainty for Infinite Sets -- 6.3. Generalized Hartley Measure in Dempster-Shafer Theory -- 6.3.1. Joint and Marginal Generalized Hartley Measures -- 6.3.2. Monotonicity of the Generalized Hartley Measure -- 6.3.3. Conditional Generalized Hartley Measures -- 6.4. Generalized Hartley Measure for Convex Sets of Probability Distributions -- 6.5. Generalized Shannon Measure in Dempster-Shafer Theory -- 6.6. Aggregate Uncertainty in Dempster-Shafer Theory -- 6.6.1. General Algorithm for Computing the Aggregate Uncertainty -- 6.6.2. Computing the Aggregated Uncertainty in Possibility Theory -- 6.7. Aggregate Uncertainty for Convex Sets of Probability Distributions -- 6.8. Disaggregated Total Uncertainty -- 6.9. Generalized Shannon Entropy -- 6.10. Alternative View of Disaggregated Total Uncertainty -- 6.11. Unifying Features of Uncertainty Measures -- Notes -- Exercises -- 7 Fuzzy Set Theory -- 7.1. An Overview -- 7.2. Basic Concepts of Standard Fuzzy Sets -- 7.3. Operations on Standard Fuzzy Sets -- 7.3.1. Complementation Operations -- 7.3.2. Intersection and Union Operations -- 7.3.3. Combinations of Basic Operations.
7.3.4. Other Operations -- 7.4. Fuzzy Numbers and Intervals -- 7.4.1. Standard Fuzzy Arithmetic -- 7.4.2. Constrained Fuzzy Arithmetic -- 7.5. Fuzzy Relations -- 7.5.1. Projections and Cylindric Extensions -- 7.5.2. Compositions, Joins, and Inverses -- 7.6. Fuzzy Logic -- 7.6.1. Fuzzy Propositions -- 7.6.2. Approximate Reasoning -- 7.7. Fuzzy Systems -- 7.7.1. Granulation -- 7.7.2. Types of Fuzzy Systems -- 7.7.3. Defuzzification -- 7.8. Nonstandard Fuzzy Sets -- 7.9. Constructing Fuzzy Sets and Operations -- Notes -- Exercises -- 8 Fuzzification of Uncertainty Theories -- 8.1. Aspects of Fuzzification -- 8.2. Measures of Fuzziness -- 8.3. Fuzzy-Set Interpretation of Possibility Theory -- 8.4. Probabilities of Fuzzy Events -- 8.5. Fuzzification of Reachable Interval-Valued Probability Distributions -- 8.6. Other Fuzzification Efforts -- Notes -- Exercises -- 9 Methodological Issues -- 9.1. An Overview -- 9.2. Principle of Minimum Uncertainty -- 9.2.1. Simplification Problems -- 9.2.2. Conflict-Resolution Problems -- 9.3. Principle of Maximum Uncertainty -- 9.3.1. Principle of Maximum Entropy -- 9.3.2. Principle of Maximum Nonspecificity -- 9.3.3. Principle of Maximum Uncertainty in GIT -- 9.4. Principle of Requisite Generalization -- 9.5. Principle of Uncertainty Invariance -- 9.5.1. Computationally Simple Approximations -- 9.5.2. Probability-Possibility Transformations -- 9.5.3. Approximations of Belief Functions by Necessity Functions -- 9.5.4. Transformations Between l-Measures and Possibility Measures -- 9.5.5. Approximations of Graded Possibilities by Crisp Possibilities -- Notes -- Exercises -- 10 Conclusions -- 10.1. Summary and Assessment of Results in Generalized Information Theory -- 10.2. Main Issues of Current Interest -- 10.3. Long-Term Research Areas -- 10.4. Significance of GIT -- Notes -- Appendix A Uniqueness of the U-Uncertainty -- Appendix B Uniqueness of Generalized Hartley Measure in the Dempster-Shafer Theory -- Appendix C Correctness of Algorithm 6.1.
Appendix D Proper Range of GeneralizedShannon Entropy -- Appendix E Maximum of GSa in Section 6.9 -- Appendix F Glossary of Key Concepts -- Appendix G Glossary of Symbols -- Bibliography -- Subject Index -- Name Index.
Record Nr. UNISA-996202351503316
Klir George J. <1932->  
Hoboken, New Jersey : , : Wiley-Interscience, , c2006
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Uncertainty and information : foundations of generalized information theory / / George J. Klir
Uncertainty and information : foundations of generalized information theory / / George J. Klir
Autore Klir George J. <1932->
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley-Interscience, , c2006
Descrizione fisica 1 online resource (519 p.)
Disciplina 003.54
003/.54
Soggetto topico Uncertainty (Information theory)
Fuzzy systems
ISBN 1-280-24298-1
9786610242986
0-470-31574-1
0-471-75557-5
0-471-75556-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgments -- 1 Introduction -- 1.1. Uncertainty and Its Significance -- 1.2. Uncertainty-Based Information -- 1.3. Generalized Information Theory -- 1.4. Relevant Terminology and Notation -- 1.5. An Outline of the Book -- Notes -- Exercises -- 2 Classical Possibility-Based Uncertainty Theory -- 2.1. Possibility and Necessity Functions -- 2.2. Hartley Measure of Uncertainty for Finite Sets -- 2.2.1. Simple Derivation of the Hartley Measure -- 2.2.2. Uniqueness of the Hartley Measure -- 2.2.3. Basic Properties of the Hartley Measure -- 2.2.4. Examples -- 2.3. Hartley-Like Measure of Uncertainty for Infinite Sets -- 2.3.1. Definition -- 2.3.2. Required Properties -- 2.3.3. Examples -- Notes -- Exercises -- 3 Classical Probability-Based Uncertainty Theory -- 3.1. Probability Functions -- 3.1.1. Functions on Finite Sets -- 3.1.2. Functions on Infinite Sets -- 3.1.3. Bayes' Theorem -- 3.2. Shannon Measure of Uncertainty for Finite Sets -- 3.2.1. Simple Derivation of the Shannon Entropy -- 3.2.2. Uniqueness of the Shannon Entropy -- 3.2.3. Basic Properties of the Shannon Entropy -- 3.2.4. Examples -- 3.3. Shannon-Like Measure of Uncertainty for Infinite Sets -- Notes -- Exercises -- 4 Generalized Measures and Imprecise Probabilities -- 4.1. Monotone Measures -- 4.2. Choquet Capacities -- 4.2.1. Mbius Representation -- 4.3. Imprecise Probabilities: General Principles -- 4.3.1. Lower and Upper Probabilities -- 4.3.2. Alternating Choquet Capacities -- 4.3.3. Interaction Representation -- 4.3.4. Mbius Representation -- 4.3.5. Joint and Marginal Imprecise Probabilities -- 4.3.6. Conditional Imprecise Probabilities -- 4.3.7. Noninteraction of Imprecise Probabilities -- 4.4. Arguments for Imprecise Probabilities -- 4.5. Choquet Integral -- 4.6. Unifying Features of Imprecise Probabilities -- Notes -- Exercises -- 5 Special Theories of Imprecise Probabilities -- 5.1. An Overview -- 5.2. Graded Possibilities -- 5.2.1. Mbius Representation -- 5.2.2. Ordering of Possibility Profiles.
5.2.3. Joint and Marginal Possibilities -- 5.2.4. Conditional Possibilities -- 5.2.5. Possibilities on Infinite Sets -- 5.2.6. Some Interpretations of Graded Possibilities -- 5.3. Sugeno l-Measures -- 5.3.1. Mbius Representation -- 5.4. Belief and Plausibility Measures -- 5.4.1. Joint and Marginal Bodies of Evidence -- 5.4.2. Rules of Combination -- 5.4.3. Special Classes of Bodies of Evidence -- 5.5. Reachable Interval-Valued Probability Distributions -- 5.5.1. Joint and Marginal Interval-Valued Probability Distributions -- 5.6. Other Types of Monotone Measures -- Notes -- Exercises -- 6 Measures of Uncertainty and Information -- 6.1. General Discussion -- 6.2. Generalized Hartley Measure for Graded Possibilities -- 6.2.1. Joint and Marginal U-Uncertainties -- 6.2.2. Conditional U-Uncertainty -- 6.2.3. Axiomatic Requirements for the U-Uncertainty -- 6.2.4. U-Uncertainty for Infinite Sets -- 6.3. Generalized Hartley Measure in Dempster-Shafer Theory -- 6.3.1. Joint and Marginal Generalized Hartley Measures -- 6.3.2. Monotonicity of the Generalized Hartley Measure -- 6.3.3. Conditional Generalized Hartley Measures -- 6.4. Generalized Hartley Measure for Convex Sets of Probability Distributions -- 6.5. Generalized Shannon Measure in Dempster-Shafer Theory -- 6.6. Aggregate Uncertainty in Dempster-Shafer Theory -- 6.6.1. General Algorithm for Computing the Aggregate Uncertainty -- 6.6.2. Computing the Aggregated Uncertainty in Possibility Theory -- 6.7. Aggregate Uncertainty for Convex Sets of Probability Distributions -- 6.8. Disaggregated Total Uncertainty -- 6.9. Generalized Shannon Entropy -- 6.10. Alternative View of Disaggregated Total Uncertainty -- 6.11. Unifying Features of Uncertainty Measures -- Notes -- Exercises -- 7 Fuzzy Set Theory -- 7.1. An Overview -- 7.2. Basic Concepts of Standard Fuzzy Sets -- 7.3. Operations on Standard Fuzzy Sets -- 7.3.1. Complementation Operations -- 7.3.2. Intersection and Union Operations -- 7.3.3. Combinations of Basic Operations.
7.3.4. Other Operations -- 7.4. Fuzzy Numbers and Intervals -- 7.4.1. Standard Fuzzy Arithmetic -- 7.4.2. Constrained Fuzzy Arithmetic -- 7.5. Fuzzy Relations -- 7.5.1. Projections and Cylindric Extensions -- 7.5.2. Compositions, Joins, and Inverses -- 7.6. Fuzzy Logic -- 7.6.1. Fuzzy Propositions -- 7.6.2. Approximate Reasoning -- 7.7. Fuzzy Systems -- 7.7.1. Granulation -- 7.7.2. Types of Fuzzy Systems -- 7.7.3. Defuzzification -- 7.8. Nonstandard Fuzzy Sets -- 7.9. Constructing Fuzzy Sets and Operations -- Notes -- Exercises -- 8 Fuzzification of Uncertainty Theories -- 8.1. Aspects of Fuzzification -- 8.2. Measures of Fuzziness -- 8.3. Fuzzy-Set Interpretation of Possibility Theory -- 8.4. Probabilities of Fuzzy Events -- 8.5. Fuzzification of Reachable Interval-Valued Probability Distributions -- 8.6. Other Fuzzification Efforts -- Notes -- Exercises -- 9 Methodological Issues -- 9.1. An Overview -- 9.2. Principle of Minimum Uncertainty -- 9.2.1. Simplification Problems -- 9.2.2. Conflict-Resolution Problems -- 9.3. Principle of Maximum Uncertainty -- 9.3.1. Principle of Maximum Entropy -- 9.3.2. Principle of Maximum Nonspecificity -- 9.3.3. Principle of Maximum Uncertainty in GIT -- 9.4. Principle of Requisite Generalization -- 9.5. Principle of Uncertainty Invariance -- 9.5.1. Computationally Simple Approximations -- 9.5.2. Probability-Possibility Transformations -- 9.5.3. Approximations of Belief Functions by Necessity Functions -- 9.5.4. Transformations Between l-Measures and Possibility Measures -- 9.5.5. Approximations of Graded Possibilities by Crisp Possibilities -- Notes -- Exercises -- 10 Conclusions -- 10.1. Summary and Assessment of Results in Generalized Information Theory -- 10.2. Main Issues of Current Interest -- 10.3. Long-Term Research Areas -- 10.4. Significance of GIT -- Notes -- Appendix A Uniqueness of the U-Uncertainty -- Appendix B Uniqueness of Generalized Hartley Measure in the Dempster-Shafer Theory -- Appendix C Correctness of Algorithm 6.1.
Appendix D Proper Range of GeneralizedShannon Entropy -- Appendix E Maximum of GSa in Section 6.9 -- Appendix F Glossary of Key Concepts -- Appendix G Glossary of Symbols -- Bibliography -- Subject Index -- Name Index.
Record Nr. UNINA-9910830850103321
Klir George J. <1932->  
Hoboken, New Jersey : , : Wiley-Interscience, , c2006
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