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Acoustic Cavitation and Bubble Dynamics [[electronic resource] /] / by Kyuichi Yasui
Acoustic Cavitation and Bubble Dynamics [[electronic resource] /] / by Kyuichi Yasui
Autore Yasui Kyuichi
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (VIII, 124 p. 84 illus.)
Disciplina 530.4275
Collana Ultrasound and Sonochemistry
Soggetto topico Chemometrics
Chemistry, Physical and theoretical
Acoustics
Fluid mechanics
Math. Applications in Chemistry
Theoretical and Computational Chemistry
Engineering Fluid Dynamics
ISBN 3-319-68237-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Acoustic Cavitation -- Bubble Dynamics -- Unsolved Problems.
Record Nr. UNINA-9910298589103321
Yasui Kyuichi  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Adaptive Algorithms and Stochastic Approximations [[electronic resource] /] / by Albert Benveniste, Michel Metivier, Pierre Priouret
Adaptive Algorithms and Stochastic Approximations [[electronic resource] /] / by Albert Benveniste, Michel Metivier, Pierre Priouret
Autore Benveniste Albert
Edizione [1st ed. 1990.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1990
Descrizione fisica 1 online resource (XII, 364 p.)
Disciplina 519.2
Collana Stochastic Modelling and Applied Probability
Soggetto topico Probabilities
Chemometrics
Computational intelligence
Probability Theory and Stochastic Processes
Math. Applications in Chemistry
Computational Intelligence
ISBN 3-642-75894-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto I. Adaptive Algorithms: Applications -- 1. General Adaptive Algorithm Form -- 2. Convergence: the ODE Method -- 3. Rate of Convergence -- 4. Tracking Non-Stationary Parameters -- 5. Sequential Detection; Model Validation -- 6. Appendices to Part I -- II. Stochastic Approximations: Theory -- 1. O.D.E. and Convergence A.S. for an Algorithm with Locally Bounded Moments -- 2. Application to the Examples of Part I -- 3. Analysis of the Algorithm in the General Case -- 4. Gaussian Approximations to the Algorithms -- 5. Appendix to Part II: A Simple Theorem in the “Robbins-Monro” Case -- Subject Index to Part I -- Subject Index to Part II.
Record Nr. UNINA-9910480530803321
Benveniste Albert  
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1990
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Adaptive Algorithms and Stochastic Approximations [[electronic resource] /] / by Albert Benveniste, Michel Metivier, Pierre Priouret
Adaptive Algorithms and Stochastic Approximations [[electronic resource] /] / by Albert Benveniste, Michel Metivier, Pierre Priouret
Autore Benveniste Albert
Edizione [1st ed. 1990.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1990
Descrizione fisica 1 online resource (XII, 364 p.)
Disciplina 519.2
Collana Stochastic Modelling and Applied Probability
Soggetto topico Probabilities
Chemometrics
Computational intelligence
Probability Theory and Stochastic Processes
Math. Applications in Chemistry
Computational Intelligence
ISBN 3-642-75894-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto I. Adaptive Algorithms: Applications -- 1. General Adaptive Algorithm Form -- 2. Convergence: the ODE Method -- 3. Rate of Convergence -- 4. Tracking Non-Stationary Parameters -- 5. Sequential Detection; Model Validation -- 6. Appendices to Part I -- II. Stochastic Approximations: Theory -- 1. O.D.E. and Convergence A.S. for an Algorithm with Locally Bounded Moments -- 2. Application to the Examples of Part I -- 3. Analysis of the Algorithm in the General Case -- 4. Gaussian Approximations to the Algorithms -- 5. Appendix to Part II: A Simple Theorem in the “Robbins-Monro” Case -- Subject Index to Part I -- Subject Index to Part II.
Record Nr. UNINA-9910789215503321
Benveniste Albert  
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1990
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Adaptive Algorithms and Stochastic Approximations [[electronic resource] /] / by Albert Benveniste, Michel Metivier, Pierre Priouret
Adaptive Algorithms and Stochastic Approximations [[electronic resource] /] / by Albert Benveniste, Michel Metivier, Pierre Priouret
Autore Benveniste Albert
Edizione [1st ed. 1990.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1990
Descrizione fisica 1 online resource (XII, 364 p.)
Disciplina 519.2
Collana Stochastic Modelling and Applied Probability
Soggetto topico Probabilities
Chemometrics
Computational intelligence
Probability Theory and Stochastic Processes
Math. Applications in Chemistry
Computational Intelligence
ISBN 3-642-75894-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto I. Adaptive Algorithms: Applications -- 1. General Adaptive Algorithm Form -- 2. Convergence: the ODE Method -- 3. Rate of Convergence -- 4. Tracking Non-Stationary Parameters -- 5. Sequential Detection; Model Validation -- 6. Appendices to Part I -- II. Stochastic Approximations: Theory -- 1. O.D.E. and Convergence A.S. for an Algorithm with Locally Bounded Moments -- 2. Application to the Examples of Part I -- 3. Analysis of the Algorithm in the General Case -- 4. Gaussian Approximations to the Algorithms -- 5. Appendix to Part II: A Simple Theorem in the “Robbins-Monro” Case -- Subject Index to Part I -- Subject Index to Part II.
Record Nr. UNINA-9910807086703321
Benveniste Albert  
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 1990
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Topics in Shannon Sampling and Interpolation Theory [[electronic resource] /] / edited by Robert J.II Marks
Advanced Topics in Shannon Sampling and Interpolation Theory [[electronic resource] /] / edited by Robert J.II Marks
Edizione [1st ed. 1993.]
Pubbl/distr/stampa New York, NY : , : Springer New York : , : Imprint : Springer, , 1993
Descrizione fisica 1 online resource (XIII, 360 p.)
Disciplina 621.3
Collana Springer Texts in Electrical Engineering
Soggetto topico Electrical engineering
Computers
Chemometrics
Computational intelligence
Electrical Engineering
Models and Principles
Math. Applications in Chemistry
Computational Intelligence
ISBN 1-4613-9757-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1 Gabor’s Signal Expansion and Its Relation to Sampling of the Sliding-Window Spectrum -- 1.1 Introduction -- 1.2 Sliding-Window Spectrum -- 1.3 Sampling Theorem for the Sliding-Window Spectrum -- 1.4 Examples of Window Functions -- 1.5 Gabor’s Signal Expansion -- 1.6 Examples of Elementary Signals -- 1.7 Degrees of Freedom of a Signal -- 1.8 Optical Generation of Gabor’s Expansion Coefficients for Rastered Signals -- 1.9 Conclusion -- 2 Sampling in Optics -- 2.1 Introduction -- 2.2 Historical Background -- 2.3 The von Laue Analysis -- 2.4 Degrees of Freedom of an Image -- 2.5 Superresolving Pupils -- 2.6 Fresnel SampHng -- 2.7 Exponential SampHng -- 2.8 Partially Coherent Fields -- 2.9 Optical Processing -- 2.10 Conclusion -- 3 A Multidimensional Extension of Papoulis’ Generalized Sampling Expansion with the Application in Minimum Density Sampling -- I: A Multidimensional Extension of Papoulis’ Generalized Sampling Expansion -- 3.1 Introduction -- 3.2 GSE Formulation -- 3.3 M-D Extension -- 3.4 Extension Generalization -- 3.5 Conclusion -- II: Sampling Multidimensional Band-Limited Functions At Minimum Densities -- 3.6 Sample Interdependency -- 3.7 Sampling Density Reduction Using M-D GSE -- 3.8 Computational Complexity of the Two Formulations -- 3.9 Sampling at the Minimum Density -- 3.10 Discussion -- 3.11 Conclusion -- 4 Nonuniform Sampling -- 4.1 Preliminary Discussions -- 4.2 General Nonuniform Sampling Theorems -- 4.3 Spectral Analysis of Nonuniform Samples and Signal Recovery -- 4.4 Discussion on Reconstruction Methods -- 5 Linear Prediction by Samples from the Past -- 5.1 Preliminaries -- 5.2 Prediction of Deterministic Signals -- 5.3 Prediction of Random Signals -- 6 Polar, Spiral, and Generalized Sampling and Interpolation -- 6.1 Introduction -- 6.2 Sampling in Polar Coordinates -- 6.3 Spiral Sampling -- 6.4 Reconstruction from Non-Uniform Samples by Convex Projections -- 6.5 Experimental Results -- 6.6 Conclusions -- Appendix A -- Appendix B -- 7 Error Analysis in Application of Generalizations of the Sampling Theorem -- Foreword: Welcomed General Sources for the Sampling Theorems -- 7.1 Introduction — Sampling Theorems -- 7.2 Error Bounds of the Present Extension of the Sampling Theorem -- 7.3 Applications -- Appendix A -- A.1 Analysis of Gibbs’ Phenomena.
Record Nr. UNINA-9910478906503321
New York, NY : , : Springer New York : , : Imprint : Springer, , 1993
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Topics in Shannon Sampling and Interpolation Theory [[electronic resource] /] / edited by Robert J.II Marks
Advanced Topics in Shannon Sampling and Interpolation Theory [[electronic resource] /] / edited by Robert J.II Marks
Edizione [1st ed. 1993.]
Pubbl/distr/stampa New York, NY : , : Springer New York : , : Imprint : Springer, , 1993
Descrizione fisica 1 online resource (XIII, 360 p.)
Disciplina 621.3
Collana Springer Texts in Electrical Engineering
Soggetto topico Electrical engineering
Computers
Chemometrics
Computational intelligence
Electrical Engineering
Models and Principles
Math. Applications in Chemistry
Computational Intelligence
ISBN 1-4613-9757-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1 Gabor’s Signal Expansion and Its Relation to Sampling of the Sliding-Window Spectrum -- 1.1 Introduction -- 1.2 Sliding-Window Spectrum -- 1.3 Sampling Theorem for the Sliding-Window Spectrum -- 1.4 Examples of Window Functions -- 1.5 Gabor’s Signal Expansion -- 1.6 Examples of Elementary Signals -- 1.7 Degrees of Freedom of a Signal -- 1.8 Optical Generation of Gabor’s Expansion Coefficients for Rastered Signals -- 1.9 Conclusion -- 2 Sampling in Optics -- 2.1 Introduction -- 2.2 Historical Background -- 2.3 The von Laue Analysis -- 2.4 Degrees of Freedom of an Image -- 2.5 Superresolving Pupils -- 2.6 Fresnel SampHng -- 2.7 Exponential SampHng -- 2.8 Partially Coherent Fields -- 2.9 Optical Processing -- 2.10 Conclusion -- 3 A Multidimensional Extension of Papoulis’ Generalized Sampling Expansion with the Application in Minimum Density Sampling -- I: A Multidimensional Extension of Papoulis’ Generalized Sampling Expansion -- 3.1 Introduction -- 3.2 GSE Formulation -- 3.3 M-D Extension -- 3.4 Extension Generalization -- 3.5 Conclusion -- II: Sampling Multidimensional Band-Limited Functions At Minimum Densities -- 3.6 Sample Interdependency -- 3.7 Sampling Density Reduction Using M-D GSE -- 3.8 Computational Complexity of the Two Formulations -- 3.9 Sampling at the Minimum Density -- 3.10 Discussion -- 3.11 Conclusion -- 4 Nonuniform Sampling -- 4.1 Preliminary Discussions -- 4.2 General Nonuniform Sampling Theorems -- 4.3 Spectral Analysis of Nonuniform Samples and Signal Recovery -- 4.4 Discussion on Reconstruction Methods -- 5 Linear Prediction by Samples from the Past -- 5.1 Preliminaries -- 5.2 Prediction of Deterministic Signals -- 5.3 Prediction of Random Signals -- 6 Polar, Spiral, and Generalized Sampling and Interpolation -- 6.1 Introduction -- 6.2 Sampling in Polar Coordinates -- 6.3 Spiral Sampling -- 6.4 Reconstruction from Non-Uniform Samples by Convex Projections -- 6.5 Experimental Results -- 6.6 Conclusions -- Appendix A -- Appendix B -- 7 Error Analysis in Application of Generalizations of the Sampling Theorem -- Foreword: Welcomed General Sources for the Sampling Theorems -- 7.1 Introduction — Sampling Theorems -- 7.2 Error Bounds of the Present Extension of the Sampling Theorem -- 7.3 Applications -- Appendix A -- A.1 Analysis of Gibbs’ Phenomena.
Record Nr. UNINA-9910789217903321
New York, NY : , : Springer New York : , : Imprint : Springer, , 1993
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Topics in Shannon Sampling and Interpolation Theory [[electronic resource] /] / edited by Robert J.II Marks
Advanced Topics in Shannon Sampling and Interpolation Theory [[electronic resource] /] / edited by Robert J.II Marks
Edizione [1st ed. 1993.]
Pubbl/distr/stampa New York, NY : , : Springer New York : , : Imprint : Springer, , 1993
Descrizione fisica 1 online resource (XIII, 360 p.)
Disciplina 621.3
Collana Springer Texts in Electrical Engineering
Soggetto topico Electrical engineering
Computers
Chemometrics
Computational intelligence
Electrical Engineering
Models and Principles
Math. Applications in Chemistry
Computational Intelligence
ISBN 1-4613-9757-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1 Gabor’s Signal Expansion and Its Relation to Sampling of the Sliding-Window Spectrum -- 1.1 Introduction -- 1.2 Sliding-Window Spectrum -- 1.3 Sampling Theorem for the Sliding-Window Spectrum -- 1.4 Examples of Window Functions -- 1.5 Gabor’s Signal Expansion -- 1.6 Examples of Elementary Signals -- 1.7 Degrees of Freedom of a Signal -- 1.8 Optical Generation of Gabor’s Expansion Coefficients for Rastered Signals -- 1.9 Conclusion -- 2 Sampling in Optics -- 2.1 Introduction -- 2.2 Historical Background -- 2.3 The von Laue Analysis -- 2.4 Degrees of Freedom of an Image -- 2.5 Superresolving Pupils -- 2.6 Fresnel SampHng -- 2.7 Exponential SampHng -- 2.8 Partially Coherent Fields -- 2.9 Optical Processing -- 2.10 Conclusion -- 3 A Multidimensional Extension of Papoulis’ Generalized Sampling Expansion with the Application in Minimum Density Sampling -- I: A Multidimensional Extension of Papoulis’ Generalized Sampling Expansion -- 3.1 Introduction -- 3.2 GSE Formulation -- 3.3 M-D Extension -- 3.4 Extension Generalization -- 3.5 Conclusion -- II: Sampling Multidimensional Band-Limited Functions At Minimum Densities -- 3.6 Sample Interdependency -- 3.7 Sampling Density Reduction Using M-D GSE -- 3.8 Computational Complexity of the Two Formulations -- 3.9 Sampling at the Minimum Density -- 3.10 Discussion -- 3.11 Conclusion -- 4 Nonuniform Sampling -- 4.1 Preliminary Discussions -- 4.2 General Nonuniform Sampling Theorems -- 4.3 Spectral Analysis of Nonuniform Samples and Signal Recovery -- 4.4 Discussion on Reconstruction Methods -- 5 Linear Prediction by Samples from the Past -- 5.1 Preliminaries -- 5.2 Prediction of Deterministic Signals -- 5.3 Prediction of Random Signals -- 6 Polar, Spiral, and Generalized Sampling and Interpolation -- 6.1 Introduction -- 6.2 Sampling in Polar Coordinates -- 6.3 Spiral Sampling -- 6.4 Reconstruction from Non-Uniform Samples by Convex Projections -- 6.5 Experimental Results -- 6.6 Conclusions -- Appendix A -- Appendix B -- 7 Error Analysis in Application of Generalizations of the Sampling Theorem -- Foreword: Welcomed General Sources for the Sampling Theorems -- 7.1 Introduction — Sampling Theorems -- 7.2 Error Bounds of the Present Extension of the Sampling Theorem -- 7.3 Applications -- Appendix A -- A.1 Analysis of Gibbs’ Phenomena.
Record Nr. UNINA-9910818048003321
New York, NY : , : Springer New York : , : Imprint : Springer, , 1993
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Applications of Quantum Dynamics in Chemistry [[electronic resource] /] / by Fabien Gatti, Benjamin Lasorne, Hans-Dieter Meyer, André Nauts
Applications of Quantum Dynamics in Chemistry [[electronic resource] /] / by Fabien Gatti, Benjamin Lasorne, Hans-Dieter Meyer, André Nauts
Autore Gatti Fabien
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XVI, 429 p. 110 illus.)
Disciplina 541.28
Collana Lecture Notes in Chemistry
Soggetto topico Chemistry, Physical and theoretical
Quantum physics
Chemoinformatics
Chemometrics
Theoretical and Computational Chemistry
Quantum Physics
Computer Applications in Chemistry
Math. Applications in Chemistry
ISBN 3-319-53923-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I Introduction -- Part II Concepts and Methods: Quantum effects -- Electronic states and potential energy operators -- The Choice of coordinates -- Kinetic energy operators -- Introduction to molecular symmetry -- Introduction to numerical methods and to MCTDH -- Part III Applications: Infrared spectroscopy -- Quantum control with laser pulses in the electronic ground state -- Photodissociation spectra -- Cross sections for reactive scattering -- Quantum control with laser pulses for electronically excited states -- Non-adiabatic photochemistry -- Optimal control and quantum computers -- Part IV Conclusion.
Record Nr. UNINA-9910254147103321
Gatti Fabien  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Applied chemometrics for scientists [[electronic resource] /] / Richard G. Brereton
Applied chemometrics for scientists [[electronic resource] /] / Richard G. Brereton
Autore Brereton Richard G
Pubbl/distr/stampa Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007
Descrizione fisica 1 online resource (397 p.)
Disciplina 542.30151
543.015195
Soggetto topico Chemometrics
Chemistry, Analytic
Soggetto genere / forma Electronic books.
ISBN 1-280-83864-7
9786610838646
0-470-05778-5
0-470-05777-7
Classificazione 35.05
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Applied Chemometrics for Scientists; Contents; Preface; 1 Introduction; 1.1 Development of Chemometrics; 1.1.1 Early Developments; 1.1.2 1980s and the Borderlines between Other Disciplines; 1.1.3 1990s and Problems of Intermediate Complexity; 1.1.4 Current Developments in Complex Problem Solving; 1.2 Application Areas; 1.3 How to Use this Book; 1.4 Literature and Other Sources of Information; References; 2 Experimental Design; 2.1 Why Design Experiments in Chemistry?; 2.2 Degrees of Freedom and Sources of Error; 2.3 Analysis of Variance and Interpretation of Errors
2.4 Matrices, Vectors and the Pseudoinverse2.5 Design Matrices; 2.6 Factorial Designs; 2.6.1 Extending the Number of Factors; 2.6.2 Extending the Number of Levels; 2.7 An Example of a Factorial Design; 2.8 Fractional Factorial Designs; 2.9 Plackett-Burman and Taguchi Designs; 2.10 The Application of a Plackett-Burman Design to the Screening of Factors Influencing a Chemical Reaction; 2.11 Central Composite Designs; 2.12 Mixture Designs; 2.12.1 Simplex Centroid Designs; 2.12.2 Simplex Lattice Designs; 2.12.3 Constrained Mixture Designs
2.13 A Four Component Mixture Design Used to Study Blending of Olive Oils2.14 Simplex Optimization; 2.15 Leverage and Confidence in Models; 2.16 Designs for Multivariate Calibration; References; 3 Statistical Concepts; 3.1 Statistics for Chemists; 3.2 Errors; 3.2.1 Sampling Errors; 3.2.2 Sample Preparation Errors; 3.2.3 Instrumental Noise; 3.2.4 Sources of Error; 3.3 Describing Data; 3.3.1 Descriptive Statistics; 3.3.2 Graphical Presentation; 3.3.3 Covariance and Correlation Coefficient; 3.4 The Normal Distribution; 3.4.1 Error Distributions; 3.4.2 Normal Distribution Functions and Tables
3.4.3 Applications3.5 Is a Distribution Normal?; 3.5.1 Cumulative Frequency; 3.5.2 Kolmogorov-Smirnov Test; 3.5.3 Consequences; 3.6 Hypothesis Tests; 3.7 Comparison of Means: the t-Test; 3.8 F-Test for Comparison of Variances; 3.9 Confidence in Linear Regression; 3.9.1 Linear Calibration; 3.9.2 Example; 3.9.3 Confidence of Prediction of Parameters; 3.10 More about Confidence; 3.10.1 Confidence in the Mean; 3.10.2 Confidence in the Standard Deviation; 3.11 Consequences of Outliers and How to Deal with Them; 3.12 Detection of Outliers; 3.12.1 Normal Distributions; 3.12.2 Linear Regression
3.12.3 Multivariate Calibration3.13 Shewhart Charts; 3.14 More about Control Charts; 3.14.1 Cusum Chart; 3.14.2 Range Chart; 3.14.3 Multivariate Statistical Process Control; References; 4 Sequential Methods; 4.1 Sequential Data; 4.2 Correlograms; 4.2.1 Auto-correlograms; 4.2.2 Cross-correlograms; 4.2.3 Multivariate Correlograms; 4.3 Linear Smoothing Functions and Filters; 4.4 Fourier Transforms; 4.5 Maximum Entropy and Bayesian Methods; 4.5.1 Bayes' Theorem; 4.5.2 Maximum Entropy; 4.5.3 Maximum Entropy and Modelling; 4.6 Fourier Filters; 4.7 Peakshapes in Chromatography and Spectroscopy
4.7.1 Principal Features
Record Nr. UNINA-9910143727003321
Brereton Richard G  
Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Applied chemometrics for scientists [[electronic resource] /] / Richard G. Brereton
Applied chemometrics for scientists [[electronic resource] /] / Richard G. Brereton
Autore Brereton Richard G
Pubbl/distr/stampa Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007
Descrizione fisica 1 online resource (397 p.)
Disciplina 542.30151
543.015195
Soggetto topico Chemometrics
Chemistry, Analytic
ISBN 1-280-83864-7
9786610838646
0-470-05778-5
0-470-05777-7
Classificazione 35.05
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Applied Chemometrics for Scientists; Contents; Preface; 1 Introduction; 1.1 Development of Chemometrics; 1.1.1 Early Developments; 1.1.2 1980s and the Borderlines between Other Disciplines; 1.1.3 1990s and Problems of Intermediate Complexity; 1.1.4 Current Developments in Complex Problem Solving; 1.2 Application Areas; 1.3 How to Use this Book; 1.4 Literature and Other Sources of Information; References; 2 Experimental Design; 2.1 Why Design Experiments in Chemistry?; 2.2 Degrees of Freedom and Sources of Error; 2.3 Analysis of Variance and Interpretation of Errors
2.4 Matrices, Vectors and the Pseudoinverse2.5 Design Matrices; 2.6 Factorial Designs; 2.6.1 Extending the Number of Factors; 2.6.2 Extending the Number of Levels; 2.7 An Example of a Factorial Design; 2.8 Fractional Factorial Designs; 2.9 Plackett-Burman and Taguchi Designs; 2.10 The Application of a Plackett-Burman Design to the Screening of Factors Influencing a Chemical Reaction; 2.11 Central Composite Designs; 2.12 Mixture Designs; 2.12.1 Simplex Centroid Designs; 2.12.2 Simplex Lattice Designs; 2.12.3 Constrained Mixture Designs
2.13 A Four Component Mixture Design Used to Study Blending of Olive Oils2.14 Simplex Optimization; 2.15 Leverage and Confidence in Models; 2.16 Designs for Multivariate Calibration; References; 3 Statistical Concepts; 3.1 Statistics for Chemists; 3.2 Errors; 3.2.1 Sampling Errors; 3.2.2 Sample Preparation Errors; 3.2.3 Instrumental Noise; 3.2.4 Sources of Error; 3.3 Describing Data; 3.3.1 Descriptive Statistics; 3.3.2 Graphical Presentation; 3.3.3 Covariance and Correlation Coefficient; 3.4 The Normal Distribution; 3.4.1 Error Distributions; 3.4.2 Normal Distribution Functions and Tables
3.4.3 Applications3.5 Is a Distribution Normal?; 3.5.1 Cumulative Frequency; 3.5.2 Kolmogorov-Smirnov Test; 3.5.3 Consequences; 3.6 Hypothesis Tests; 3.7 Comparison of Means: the t-Test; 3.8 F-Test for Comparison of Variances; 3.9 Confidence in Linear Regression; 3.9.1 Linear Calibration; 3.9.2 Example; 3.9.3 Confidence of Prediction of Parameters; 3.10 More about Confidence; 3.10.1 Confidence in the Mean; 3.10.2 Confidence in the Standard Deviation; 3.11 Consequences of Outliers and How to Deal with Them; 3.12 Detection of Outliers; 3.12.1 Normal Distributions; 3.12.2 Linear Regression
3.12.3 Multivariate Calibration3.13 Shewhart Charts; 3.14 More about Control Charts; 3.14.1 Cusum Chart; 3.14.2 Range Chart; 3.14.3 Multivariate Statistical Process Control; References; 4 Sequential Methods; 4.1 Sequential Data; 4.2 Correlograms; 4.2.1 Auto-correlograms; 4.2.2 Cross-correlograms; 4.2.3 Multivariate Correlograms; 4.3 Linear Smoothing Functions and Filters; 4.4 Fourier Transforms; 4.5 Maximum Entropy and Bayesian Methods; 4.5.1 Bayes' Theorem; 4.5.2 Maximum Entropy; 4.5.3 Maximum Entropy and Modelling; 4.6 Fourier Filters; 4.7 Peakshapes in Chromatography and Spectroscopy
4.7.1 Principal Features
Record Nr. UNINA-9910830136003321
Brereton Richard G  
Chichester, England ; ; Hoboken, NJ, : John Wiley & Sons, c2007
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui