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Advances in Principal Component Analysis / / edited by Fausto Pedro García Márquez
| Advances in Principal Component Analysis / / edited by Fausto Pedro García Márquez |
| Pubbl/distr/stampa | London, United Kingdom : , : IntechOpen, , 2022 |
| Descrizione fisica | 1 online resource (252 pages) : illustrations |
| Disciplina | 519.5354 |
| Soggetto topico | Principal components analysis |
| ISBN | 1-80355-766-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. The Foundation for Open Component Analysis: A System of Systems Hyper Framework Model -- 2. Identification of Multilinear Systems: A Brief Overview -- 3. Evaluation of Principal Component Analysis Variants to Assess Their Suitability for Mobile Malware Detection -- 4. Principal Component Analysis and Artificial Intelligence Approaches for Solar Photovoltaic Power Forecasting -- 5. Variable Selection in Nonlinear Principal Component Analysis -- 6. Space-Time-Parameter PCA for Data-Driven Modeling with Application to Bioengineering -- 7. Principal Component Analysis in Financial Data Science -- 8. Determining an Adequate Number of Principal Components -- 9. Spatial Principal Component Analysis of Head-Related Transfer Functions and Its Domain Dependency -- 10. Prediction Analysis Based on Logistic Regression Modelling -- 11. On the Use of Modified Winsorization with Graphical Diagnostic for Obtaining a Statistically Optimal Classification Accuracy in Predictive Discriminant Analysis -- 12. Mode Interpretation of Aerodynamic Characteristics of Tall Buildings Subject to Twisted Winds. |
| Record Nr. | UNINA-9910633975203321 |
| London, United Kingdom : , : IntechOpen, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in principal component analysis / / edited by Fausto Pedro García Márquez
| Advances in principal component analysis / / edited by Fausto Pedro García Márquez |
| Pubbl/distr/stampa | London, England : , : IntechOpen, , 2022 |
| Descrizione fisica | 1 online resource (252 pages) |
| Disciplina | 519.5354 |
| Soggetto topico |
Principal components analysis
Correspondence analysis (Statistics) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. The Foundation for Open Component Analysis: A System of Systems Hyper Framework Model -- 2. Identification of Multilinear Systems: A Brief Overview -- 3. Evaluation of Principal Component Analysis Variants to Assess Their Suitability for Mobile Malware Detection -- 4. Principal Component Analysis and Artificial Intelligence Approaches for Solar Photovoltaic Power Forecasting -- 5. Variable Selection in Nonlinear Principal Component Analysis -- 6. Space-Time-Parameter PCA for Data-Driven Modeling with Application to Bioengineering -- 7. Principal Component Analysis in Financial Data Science -- 8. Determining an Adequate Number of Principal Components -- 9. Spatial Principal Component Analysis of Head-Related Transfer Functions and Its Domain Dependency -- 10. Prediction Analysis Based on Logistic Regression Modelling -- 11. On the Use of Modified Winsorization with Graphical Diagnostic for Obtaining a Statistically Optimal Classification Accuracy in Predictive Discriminant Analysis -- 12. Mode Interpretation of Aerodynamic Characteristics of Tall Buildings Subject to Twisted Winds. |
| Record Nr. | UNINA-9910688391503321 |
| London, England : , : IntechOpen, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied multiway data analysis [[electronic resource] /] / Pieter M. Kroonenberg
| Applied multiway data analysis [[electronic resource] /] / Pieter M. Kroonenberg |
| Autore | Kroonenberg Pieter M |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2008 |
| Descrizione fisica | 1 online resource (614 p.) |
| Disciplina |
519.5
519.5/35 519.535 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Multivariate analysis
Multiple comparisons (Statistics) Principal components analysis |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-23734-5
9786611237349 0-470-23800-3 0-470-23799-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
APPLIED MULTIWAY DATA ANALYSIS; CONTENTS; Foreword; Preface; PART I DATA, MODELS, AND ALGORITHMS; 1 Overture; 1.1 Three-way and multiway data; 1.2 Multiway data analysis; 1.3 Before the arrival of three-mode analysis; 1.4 Three-mode data-analytic techniques; 1.5 Example: Judging Chopin's preludes; 1.6 Birth of the Tucker model; 1.7 Current status of multiway analysis; 2 Overview; 2.1 What are multiway data?; 2.2 Why multiway analysis?; 2.3 What is a model?; 2.4 Some history; 2.5 Multiway models and methods; 2.6 Conclusions; 3 Three-Way and Multiway Data; 3.1 Chapter preview; 3.2 Terminology
3.3 Two-way solutions to three-way data3.4 Classification principles; 3.5 Overview of three-way data designs; 3.6 Fully crossed designs; 3.7 Nested designs; 3.8 Scaling designs; 3.9 Categorical data; 4 Component Models for Fully-Crossed Designs; 4.1 Introduction; 4.2 Chapter preview; 4.3 Two-mode modeling of three-way data; 4.4 Extending two-mode component models to three-mode models; 4.5 Tucker models; 4.6 Parafac models; 4.7 ParaTuck2 model; 4.8 Core arrays; 4.9 Relationships between component models; 4.10 Multiway component modeling under constraints; 4.11 Conclusions 5 Algorithms for Multiway Models5.1 Introduction; 5.2 Chapter preview; 5.3 Terminology and general issues; 5.4 An example of an iterative algorithm; 5.5 General behavior of multiway algorithms; 5.6 The Parallel factor model - Parafac; 5.7 The Tucker models; 5.8 STATIS; 5.9 Conclusions; PART II DATA HANDLING, MODEL SELECTION, AND INTERPRETATION; 6 Preprocessing; 6.1 Introduction; 6.2 Chapter preview; 6.3 General considerations; 6.4 Model-based arguments for preprocessing choices; 6.5 Content-based arguments for preprocessing choices; 6.6 Preprocessing and specific multiway data designs 6.7 Centering and analysis-of-variance models: Two-way data6.8 Centering and analysis-of-variance models: Three-way data; 6.9 Recommendations; 7 Missing Data in Multiway Analysis; 7.1 Introduction; 7.2 Chapter preview; 7.3 Handling missing data in two-mode PCA; 7.4 Handling missing data in multiway analysis; 7.5 Multiple imputation in multiway analysis: Data matters; 7.6 Missing data in multiway analysis: Practice; 7.7 Example: Spanjer's Chromatography data; 7.8 Example: NICHD Child care data; 7.9 Further applications; 7.10 Computer programs for multiple imputation 8 Model and Dimensionality Selection8.1 Introduction; 8.2 Chapter preview; 8.3 Sample size and stochastics; 8.4 Degrees of freedom; 8.5 Selecting the dimensionality of a Tucker model; 8.6 Selecting the dimensionality of a Parafac model; 8.7 Model selection from a hierarchy; 8.8 Model stability and predictive power; 8.9 Example: Chopin prelude data; 8.10 Conclusions; 9 Interpreting Component Models; 9.1 Chapter preview; 9.2 General principles; 9.3 Representations of component models; 9.4 Scaling of components; 9.5 Interpreting core arrays; 9.6 Interpreting extended core arrays 9.7 Special topics |
| Record Nr. | UNINA-9910145562403321 |
Kroonenberg Pieter M
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| Hoboken, N.J., : Wiley-Interscience, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied multiway data analysis / / Pieter M. Kroonenberg
| Applied multiway data analysis / / Pieter M. Kroonenberg |
| Autore | Kroonenberg Pieter M |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2008 |
| Descrizione fisica | 1 online resource (614 p.) |
| Disciplina | 519.5/35 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Multivariate analysis
Multiple comparisons (Statistics) Principal components analysis |
| ISBN |
1-281-23734-5
9786611237349 0-470-23800-3 0-470-23799-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
APPLIED MULTIWAY DATA ANALYSIS; CONTENTS; Foreword; Preface; PART I DATA, MODELS, AND ALGORITHMS; 1 Overture; 1.1 Three-way and multiway data; 1.2 Multiway data analysis; 1.3 Before the arrival of three-mode analysis; 1.4 Three-mode data-analytic techniques; 1.5 Example: Judging Chopin's preludes; 1.6 Birth of the Tucker model; 1.7 Current status of multiway analysis; 2 Overview; 2.1 What are multiway data?; 2.2 Why multiway analysis?; 2.3 What is a model?; 2.4 Some history; 2.5 Multiway models and methods; 2.6 Conclusions; 3 Three-Way and Multiway Data; 3.1 Chapter preview; 3.2 Terminology
3.3 Two-way solutions to three-way data3.4 Classification principles; 3.5 Overview of three-way data designs; 3.6 Fully crossed designs; 3.7 Nested designs; 3.8 Scaling designs; 3.9 Categorical data; 4 Component Models for Fully-Crossed Designs; 4.1 Introduction; 4.2 Chapter preview; 4.3 Two-mode modeling of three-way data; 4.4 Extending two-mode component models to three-mode models; 4.5 Tucker models; 4.6 Parafac models; 4.7 ParaTuck2 model; 4.8 Core arrays; 4.9 Relationships between component models; 4.10 Multiway component modeling under constraints; 4.11 Conclusions 5 Algorithms for Multiway Models5.1 Introduction; 5.2 Chapter preview; 5.3 Terminology and general issues; 5.4 An example of an iterative algorithm; 5.5 General behavior of multiway algorithms; 5.6 The Parallel factor model - Parafac; 5.7 The Tucker models; 5.8 STATIS; 5.9 Conclusions; PART II DATA HANDLING, MODEL SELECTION, AND INTERPRETATION; 6 Preprocessing; 6.1 Introduction; 6.2 Chapter preview; 6.3 General considerations; 6.4 Model-based arguments for preprocessing choices; 6.5 Content-based arguments for preprocessing choices; 6.6 Preprocessing and specific multiway data designs 6.7 Centering and analysis-of-variance models: Two-way data6.8 Centering and analysis-of-variance models: Three-way data; 6.9 Recommendations; 7 Missing Data in Multiway Analysis; 7.1 Introduction; 7.2 Chapter preview; 7.3 Handling missing data in two-mode PCA; 7.4 Handling missing data in multiway analysis; 7.5 Multiple imputation in multiway analysis: Data matters; 7.6 Missing data in multiway analysis: Practice; 7.7 Example: Spanjer's Chromatography data; 7.8 Example: NICHD Child care data; 7.9 Further applications; 7.10 Computer programs for multiple imputation 8 Model and Dimensionality Selection8.1 Introduction; 8.2 Chapter preview; 8.3 Sample size and stochastics; 8.4 Degrees of freedom; 8.5 Selecting the dimensionality of a Tucker model; 8.6 Selecting the dimensionality of a Parafac model; 8.7 Model selection from a hierarchy; 8.8 Model stability and predictive power; 8.9 Example: Chopin prelude data; 8.10 Conclusions; 9 Interpreting Component Models; 9.1 Chapter preview; 9.2 General principles; 9.3 Representations of component models; 9.4 Scaling of components; 9.5 Interpreting core arrays; 9.6 Interpreting extended core arrays 9.7 Special topics |
| Record Nr. | UNINA-9910876930003321 |
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Kroonenberg Pieter M
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| Hoboken, N.J., : Wiley-Interscience, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Comparison tools for assessing the microgravity environment of missions, carriers and conditions / / Richard DeLombard [and three others]
| Comparison tools for assessing the microgravity environment of missions, carriers and conditions / / Richard DeLombard [and three others] |
| Autore | DeLombard Richard |
| Pubbl/distr/stampa | Cleveland, Ohio : , : National Aeronautics and Space Administration, Lewis Research Center, , April 1997 |
| Descrizione fisica | 1 online resource (vii, 53 pages) : illustrations |
| Collana | NASA TM |
| Soggetto topico |
Microgravity
Acceleration measurement Principal components analysis Spectrum analysis Spacecraft environments |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910707608903321 |
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DeLombard Richard
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| Cleveland, Ohio : , : National Aeronautics and Space Administration, Lewis Research Center, , April 1997 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Constrained principal component analysis and related techniques / / Yoshio Takane, Professor Emeritus, McGill University Montreal, Quebec, Canada and Adjunct Professor at University of Victoria British Columbia, Canada
| Constrained principal component analysis and related techniques / / Yoshio Takane, Professor Emeritus, McGill University Montreal, Quebec, Canada and Adjunct Professor at University of Victoria British Columbia, Canada |
| Autore | Takane Yoshio |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton : , : Chapman and Hall/CRC, , 2014 |
| Descrizione fisica | 1 online resource (244 p.) |
| Disciplina | 519.5/35 |
| Collana | Monographs on statistics and applied probability |
| Soggetto topico |
Principal components analysis
Multivariate analysis |
| ISBN |
0-429-18837-4
1-4665-5666-8 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Contents; List of Figures; List of Tables; Preface; About the Author; Chapter 1 Introduction; Chapter 2 Mathematical Foundation; Chapter 3 Constrained Principal Component Analysis (CPCA); Chapter 4 Special Cases and Related Methods; Chapter 5 Related Topics of Interest; Chapter 6 Different Constraints on Different Dimensions (DCDD); Epilogue; Appendix; Bibliography; Back Cover |
| Record Nr. | UNINA-9910787586203321 |
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Takane Yoshio
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| Boca Raton : , : Chapman and Hall/CRC, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Constrained principal component analysis and related techniques / / Yoshio Takane, Professor Emeritus, McGill University Montreal, Quebec, Canada and Adjunct Professor at University of Victoria British Columbia, Canada
| Constrained principal component analysis and related techniques / / Yoshio Takane, Professor Emeritus, McGill University Montreal, Quebec, Canada and Adjunct Professor at University of Victoria British Columbia, Canada |
| Autore | Takane Yoshio |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton : , : Chapman and Hall/CRC, , 2014 |
| Descrizione fisica | 1 online resource (244 p.) |
| Disciplina | 519.5/35 |
| Collana | Monographs on statistics and applied probability |
| Soggetto topico |
Principal components analysis
Multivariate analysis |
| ISBN |
0-429-18837-4
1-4665-5666-8 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Contents; List of Figures; List of Tables; Preface; About the Author; Chapter 1 Introduction; Chapter 2 Mathematical Foundation; Chapter 3 Constrained Principal Component Analysis (CPCA); Chapter 4 Special Cases and Related Methods; Chapter 5 Related Topics of Interest; Chapter 6 Different Constraints on Different Dimensions (DCDD); Epilogue; Appendix; Bibliography; Back Cover |
| Record Nr. | UNINA-9910799902203321 |
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Takane Yoshio
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||
| Boca Raton : , : Chapman and Hall/CRC, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Constrained principal component analysis and related techniques / / Yoshio Takane, Professor Emeritus, McGill University Montreal, Quebec, Canada and Adjunct Professor at University of Victoria British Columbia, Canada
| Constrained principal component analysis and related techniques / / Yoshio Takane, Professor Emeritus, McGill University Montreal, Quebec, Canada and Adjunct Professor at University of Victoria British Columbia, Canada |
| Autore | Takane Yoshio |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton : , : Chapman and Hall/CRC, , 2014 |
| Descrizione fisica | 1 online resource (244 p.) |
| Disciplina | 519.5/35 |
| Collana | Monographs on statistics and applied probability |
| Soggetto topico |
Principal components analysis
Multivariate analysis |
| ISBN |
0-429-18837-4
1-4665-5666-8 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Contents; List of Figures; List of Tables; Preface; About the Author; Chapter 1 Introduction; Chapter 2 Mathematical Foundation; Chapter 3 Constrained Principal Component Analysis (CPCA); Chapter 4 Special Cases and Related Methods; Chapter 5 Related Topics of Interest; Chapter 6 Different Constraints on Different Dimensions (DCDD); Epilogue; Appendix; Bibliography; Back Cover |
| Record Nr. | UNINA-9910816839703321 |
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Takane Yoshio
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| Boca Raton : , : Chapman and Hall/CRC, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Discrimination of objects within polarimetric imagery using principle component and cluster analysis [[electronic resource] /] / Melvin Felton ... [and others]
| Discrimination of objects within polarimetric imagery using principle component and cluster analysis [[electronic resource] /] / Melvin Felton ... [and others] |
| Pubbl/distr/stampa | Adelphi, MD : , : Army Research Laboratory, , [2007] |
| Descrizione fisica | 1 online resource (vi, 22 pages) : illustrations (some color) |
| Altri autori (Persone) | FeltonMelvin A |
| Collana | ARL-TR |
| Soggetto topico |
Polarimetry
Infrared imaging Cluster analysis Principal components analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910701472803321 |
| Adelphi, MD : , : Army Research Laboratory, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Independent component analysis / / Aapo Hyvarinen, Juha Karhunen, Erkki Oja
| Independent component analysis / / Aapo Hyvarinen, Juha Karhunen, Erkki Oja |
| Autore | Hyvarinen Aapo |
| Pubbl/distr/stampa | New York, : J. Wiley, c2001 |
| Descrizione fisica | 1 online resource (505 p.) |
| Disciplina | 519.5/35 |
| Altri autori (Persone) |
KarhunenJuha
OjaErkki |
| Collana | Adaptive and learning systems for signal processing, communications, and control |
| Soggetto topico |
Multivariate analysis
Principal components analysis |
| ISBN |
1-280-26480-2
9786610264803 0-470-30861-3 0-471-46419-8 0-471-22131-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Preface; 1 Introduction; 1.1 Linear representation of multivariate data; 1.1.1 The general statistical setting; 1.1.2 Dimension reduction methods; 1.1.3 Independence as a guiding principle; 1.2 Blind source separation; 1.2.1 Observing mixtures of unknown signals; 1.2.2 Source separation based on independence; 1.3 Independent component analysis; 1.3.1 Definition; 1.3.2 Applications; 1.3.3 How to find the independent components; 1.4 History of ICA; Part I: MATHEMATICAL PRELIMINARIES; 2 Random Vectors and Independence; 2.1 Probability distributions and densities
2.2 Expectations and moments2.3 Uncorrelatedness and independence; 2.4 Conditional densities and Bayes' rule; 2.5 The multivariate gaussian density; 2.6 Density of a transformation; 2.7 Higher-order statistics; 2.8 Stochastic processes *; 2.9 Concluding remarks and references; Problems; 3 Gradients and Optimization Methods; 3.1 Vector and matrix gradients; 3.2 Learning rules for unconstrained optimization; 3.3 Learning rules for constrained optimization; 3.4 Concluding remarks and references; Problems; 4 Estimation Theory; 4.1 Basic concepts; 4.2 Properties of estimators 4.3 Method of moments4.4 Least-squares estimation; 4.5 Maximum likelihood method; 4.6 Bayesian estimation *; 4.7 Concluding remarks and references; Problems; 5 Information Theory; 5.1 Entropy; 5.2 Mutual information; 5.3 Maximum entropy; 5.4 Negentropy; 5.5 Approximation of entropy by cumulants; 5.6 Approximation of entropy by nonpolynomial functions; 5.7 Concluding remarks and references; Problems; Appendix proofs; 6 Principal Component Analysis and Whitening; 6.1 Principal components; 6.2 PCA by on-line learning; 6.3 Factor analysis; 6.4 Whitening; 6.5 Orthogonalization 6.6 Concluding remarks and referencesProblems; Part II: BASIC INDEPENDENT COMPONENT ANALYSIS; 7 What is Independent Component Analysis?; 7.1 Motivation; 7.2 Definition of independent component analysis; 7.3 Illustration of ICA; 7.4 ICA is stronger that whitening; 7.5 Why gaussian variables are forbidden; 7.6 Concluding remarks and references; Problems; 8 ICA by Maximization of Nongaussianity; 8.1 ""Nongaussian is independent""; 8.2 Measuring nongaussianity by kurtosis; 8.3 Measuring nongaussianity by negentropy; 8.4 Estimating several independent components; 8.5 ICA and projection pursuit 8.6 Concluding remarks and referencesProblems; Appendix proofs; 9 ICA by Maximum Likelihood Estimation; 9.1 The likelihood of the ICA model; 9.2 Algorithms for maximum likelihood estimation; 9.3 The infomax principle; 9.4 Examples; 9.5 Concluding remarks and references; Problems; Appendix proofs; 10 ICA by Minimization of Mutual Information; 10.1 Defining ICA by mutual information; 10.2 Mutual information and nongaussianity; 10.3 Mutual information and likelihood; 10.4 Algorithms for minimization of mutual information; 10.5 Examples; 10.6 Concluding remarks and references; Problems 11 ICA by Tensorial Methods |
| Record Nr. | UNINA-9910143176003321 |
|
Hyvarinen Aapo
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| New York, : J. Wiley, c2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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