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Aus Fehlern Wird Man Klug : Eine genetisch-didaktische Rekonstruktion des "Messfehlers" / / Susanne Heinicke
| Aus Fehlern Wird Man Klug : Eine genetisch-didaktische Rekonstruktion des "Messfehlers" / / Susanne Heinicke |
| Autore | Heinicke Susanne |
| Pubbl/distr/stampa | Berlin : , : Logos Verlag Berlin, , 2012 |
| Descrizione fisica | 1 online resource (690 pages) : illustrations |
| Disciplina | 335.83 |
| Soggetto topico | Measurement - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN | 3-8325-9687-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Record Nr. | UNINA-9910467553703321 |
Heinicke Susanne
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| Berlin : , : Logos Verlag Berlin, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Aus Fehlern Wird Man Klug : Eine genetisch-didaktische Rekonstruktion des "Messfehlers" / / Susanne Heinicke
| Aus Fehlern Wird Man Klug : Eine genetisch-didaktische Rekonstruktion des "Messfehlers" / / Susanne Heinicke |
| Autore | Heinicke Susanne |
| Pubbl/distr/stampa | Berlin : , : Logos Verlag Berlin, , 2012 |
| Descrizione fisica | 1 online resource (690 pages) : illustrations |
| Disciplina | 335.83 |
| Soggetto topico | Measurement - Data processing |
| ISBN | 3-8325-9687-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Record Nr. | UNINA-9910795583803321 |
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Heinicke Susanne
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| Berlin : , : Logos Verlag Berlin, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Aus Fehlern Wird Man Klug : Eine genetisch-didaktische Rekonstruktion des "Messfehlers" / / Susanne Heinicke
| Aus Fehlern Wird Man Klug : Eine genetisch-didaktische Rekonstruktion des "Messfehlers" / / Susanne Heinicke |
| Autore | Heinicke Susanne |
| Pubbl/distr/stampa | Berlin : , : Logos Verlag Berlin, , 2012 |
| Descrizione fisica | 1 online resource (690 pages) : illustrations |
| Disciplina | 335.83 |
| Soggetto topico | Measurement - Data processing |
| ISBN | 3-8325-9687-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Record Nr. | UNINA-9910827618703321 |
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Heinicke Susanne
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| Berlin : , : Logos Verlag Berlin, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Automation solutions for analytical measurements : theory, concepts, and applications / / Heidi Fleischer, Kerstin Thurow
| Automation solutions for analytical measurements : theory, concepts, and applications / / Heidi Fleischer, Kerstin Thurow |
| Autore | Fleischer Heidi |
| Pubbl/distr/stampa | Weinheim, [Germany] : , : Wiley-VCH Verlag GmbH & Co. KGaA, , 2018 |
| Descrizione fisica | 1 online resource (261 pages) |
| Disciplina | 620.0044 |
| Soggetto topico | Measurement - Data processing |
| ISBN |
1-5231-1521-1
3-527-80532-X 3-527-80539-7 3-527-80529-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910270913603321 |
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Fleischer Heidi
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| Weinheim, [Germany] : , : Wiley-VCH Verlag GmbH & Co. KGaA, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Automation solutions for analytical measurements : theory, concepts, and applications / / Heidi Fleischer, Kerstin Thurow
| Automation solutions for analytical measurements : theory, concepts, and applications / / Heidi Fleischer, Kerstin Thurow |
| Autore | Fleischer Heidi |
| Pubbl/distr/stampa | Weinheim, [Germany] : , : Wiley-VCH Verlag GmbH & Co. KGaA, , 2018 |
| Descrizione fisica | 1 online resource (261 pages) |
| Disciplina | 620.0044 |
| Soggetto topico | Measurement - Data processing |
| ISBN |
1-5231-1521-1
3-527-80532-X 3-527-80539-7 3-527-80529-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910809420803321 |
|
Fleischer Heidi
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||
| Weinheim, [Germany] : , : Wiley-VCH Verlag GmbH & Co. KGaA, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Classification, parameter estimation, and state estimation [[electronic resource] ] : an engineering approach using MATLAB / / F. van der Heijden ... [et al.]
| Classification, parameter estimation, and state estimation [[electronic resource] ] : an engineering approach using MATLAB / / F. van der Heijden ... [et al.] |
| Autore | Duin Robert |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, West Sussex, Eng. ; ; Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (441 p.) |
| Disciplina |
620.0015118
681/.2 |
| Altri autori (Persone) | HeijdenFerdinand van der |
| Soggetto topico |
Engineering mathematics - Data processing
Measurement - Data processing Estimation theory - Data processing |
| ISBN |
1-280-26895-6
9786610268955 0-470-09015-4 1-60119-496-X 0-470-09014-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Classification, Parameter Estimation and State Estimation; Contents; Preface; Foreword; 1 Introduction; 1.1 The scope of the book; 1.1.1 Classification; 1.1.2 Parameter estimation; 1.1.3 State estimation; 1.1.4 Relations between the subjects; 1.2 Engineering; 1.3 The organization of the book; 1.4 References; 2 Detection and Classification; 2.1 Bayesian classification; 2.1.1 Uniform cost function and minimum error rate; 2.1.2 Normal distributed measurements; linear and quadratic classifiers; 2.2 Rejection; 2.2.1 Minimum error rate classification with reject option
2.3 Detection: the two-class case2.4 Selected bibliography; 2.5 Exercises; 3 Parameter Estimation; 3.1 Bayesian estimation; 3.1.1 MMSE estimation; 3.1.2 MAP estimation; 3.1.3 The Gaussian case with linear sensors; 3.1.4 Maximum likelihood estimation; 3.1.5 Unbiased linear MMSE estimation; 3.2 Performance of estimators; 3.2.1 Bias and covariance; 3.2.2 The error covariance of the unbiased linear MMSE estimator; 3.3 Data fitting; 3.3.1 Least squares fitting; 3.3.2 Fitting using a robust error norm; 3.3.3 Regression; 3.4 Overview of the family of estimators; 3.5 Selected bibliography 3.6 Exercises4 State Estimation; 4.1 A general framework for online estimation; 4.1.1 Models; 4.1.2 Optimal online estimation; 4.2 Continuous state variables; 4.2.1 Optimal online estimation in linear-Gaussian systems; 4.2.2 Suboptimal solutions for nonlinear systems; 4.2.3 Other filters for nonlinear systems; 4.3 Discrete state variables; 4.3.1 Hidden Markov models; 4.3.2 Online state estimation; 4.3.3 Offline state estimation; 4.4 Mixed states and the particle filter; 4.4.1 Importance sampling; 4.4.2 Resampling by selection; 4.4.3 The condensation algorithm; 4.5 Selected bibliography 4.6 Exercises5 Supervised Learning; 5.1 Training sets; 5.2 Parametric learning; 5.2.1 Gaussian distribution, mean unknown; 5.2.2 Gaussian distribution, covariance matrix unknown; 5.2.3 Gaussian distribution, mean and covariance matrix both unknown; 5.2.4 Estimation of the prior probabilities; 5.2.5 Binary measurements; 5.3 Nonparametric learning; 5.3.1 Parzen estimation and histogramming; 5.3.2 Nearest neighbour classification; 5.3.3 Linear discriminant functions; 5.3.4 The support vector classifier; 5.3.5 The feed-forward neural network; 5.4 Empirical evaluation; 5.5 References 5.6 Exercises6 Feature Extraction and Selection; 6.1 Criteria for selection and extraction; 6.1.1 Inter/intra class distance; 6.1.2 Chernoff-Bhattacharyya distance; 6.1.3 Other criteria; 6.2 Feature selection; 6.2.1 Branch-and-bound; 6.2.2 Suboptimal search; 6.2.3 Implementation issues; 6.3 Linear feature extraction; 6.3.1 Feature extraction based on the Bhattacharyya distance with Gaussian distributions; 6.3.2 Feature extraction based on inter/intra class distance; 6.4 References; 6.5 Exercises; 7 Unsupervised Learning; 7.1 Feature reduction; 7.1.1 Principal component analysis 7.1.2 Multi-dimensional scaling |
| Record Nr. | UNINA-9910143693003321 |
|
Duin Robert
|
||
| Chichester, West Sussex, Eng. ; ; Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Classification, parameter estimation, and state estimation [[electronic resource] ] : an engineering approach using MATLAB / / F. van der Heijden ... [et al.]
| Classification, parameter estimation, and state estimation [[electronic resource] ] : an engineering approach using MATLAB / / F. van der Heijden ... [et al.] |
| Autore | Duin Robert |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, West Sussex, Eng. ; ; Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (441 p.) |
| Disciplina |
620.0015118
681/.2 |
| Altri autori (Persone) | HeijdenFerdinand van der |
| Soggetto topico |
Engineering mathematics - Data processing
Measurement - Data processing Estimation theory - Data processing |
| ISBN |
1-280-26895-6
9786610268955 0-470-09015-4 1-60119-496-X 0-470-09014-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Classification, Parameter Estimation and State Estimation; Contents; Preface; Foreword; 1 Introduction; 1.1 The scope of the book; 1.1.1 Classification; 1.1.2 Parameter estimation; 1.1.3 State estimation; 1.1.4 Relations between the subjects; 1.2 Engineering; 1.3 The organization of the book; 1.4 References; 2 Detection and Classification; 2.1 Bayesian classification; 2.1.1 Uniform cost function and minimum error rate; 2.1.2 Normal distributed measurements; linear and quadratic classifiers; 2.2 Rejection; 2.2.1 Minimum error rate classification with reject option
2.3 Detection: the two-class case2.4 Selected bibliography; 2.5 Exercises; 3 Parameter Estimation; 3.1 Bayesian estimation; 3.1.1 MMSE estimation; 3.1.2 MAP estimation; 3.1.3 The Gaussian case with linear sensors; 3.1.4 Maximum likelihood estimation; 3.1.5 Unbiased linear MMSE estimation; 3.2 Performance of estimators; 3.2.1 Bias and covariance; 3.2.2 The error covariance of the unbiased linear MMSE estimator; 3.3 Data fitting; 3.3.1 Least squares fitting; 3.3.2 Fitting using a robust error norm; 3.3.3 Regression; 3.4 Overview of the family of estimators; 3.5 Selected bibliography 3.6 Exercises4 State Estimation; 4.1 A general framework for online estimation; 4.1.1 Models; 4.1.2 Optimal online estimation; 4.2 Continuous state variables; 4.2.1 Optimal online estimation in linear-Gaussian systems; 4.2.2 Suboptimal solutions for nonlinear systems; 4.2.3 Other filters for nonlinear systems; 4.3 Discrete state variables; 4.3.1 Hidden Markov models; 4.3.2 Online state estimation; 4.3.3 Offline state estimation; 4.4 Mixed states and the particle filter; 4.4.1 Importance sampling; 4.4.2 Resampling by selection; 4.4.3 The condensation algorithm; 4.5 Selected bibliography 4.6 Exercises5 Supervised Learning; 5.1 Training sets; 5.2 Parametric learning; 5.2.1 Gaussian distribution, mean unknown; 5.2.2 Gaussian distribution, covariance matrix unknown; 5.2.3 Gaussian distribution, mean and covariance matrix both unknown; 5.2.4 Estimation of the prior probabilities; 5.2.5 Binary measurements; 5.3 Nonparametric learning; 5.3.1 Parzen estimation and histogramming; 5.3.2 Nearest neighbour classification; 5.3.3 Linear discriminant functions; 5.3.4 The support vector classifier; 5.3.5 The feed-forward neural network; 5.4 Empirical evaluation; 5.5 References 5.6 Exercises6 Feature Extraction and Selection; 6.1 Criteria for selection and extraction; 6.1.1 Inter/intra class distance; 6.1.2 Chernoff-Bhattacharyya distance; 6.1.3 Other criteria; 6.2 Feature selection; 6.2.1 Branch-and-bound; 6.2.2 Suboptimal search; 6.2.3 Implementation issues; 6.3 Linear feature extraction; 6.3.1 Feature extraction based on the Bhattacharyya distance with Gaussian distributions; 6.3.2 Feature extraction based on inter/intra class distance; 6.4 References; 6.5 Exercises; 7 Unsupervised Learning; 7.1 Feature reduction; 7.1.1 Principal component analysis 7.1.2 Multi-dimensional scaling |
| Record Nr. | UNINA-9910830828303321 |
|
Duin Robert
|
||
| Chichester, West Sussex, Eng. ; ; Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Classification, parameter estimation, and state estimation : an engineering approach using MATLAB / / Bangjun Lei [and six others]
| Classification, parameter estimation, and state estimation : an engineering approach using MATLAB / / Bangjun Lei [and six others] |
| Autore | Heijden Ferdinand van der |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2017 |
| Descrizione fisica | 1 online resource (431 pages) : illustrations |
| Disciplina | 681/.2 |
| Soggetto topico |
Engineering mathematics - Data processing
Measurement - Data processing Estimation theory - Data processing |
| ISBN |
1-119-15245-3
1-119-15244-5 1-119-15248-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910270899103321 |
|
Heijden Ferdinand van der
|
||
| Hoboken, New Jersey : , : Wiley, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Classification, parameter estimation, and state estimation : an engineering approach using MATLAB / / Bangjun Lei [and six others]
| Classification, parameter estimation, and state estimation : an engineering approach using MATLAB / / Bangjun Lei [and six others] |
| Autore | Heijden Ferdinand van der |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2017 |
| Descrizione fisica | 1 online resource (431 pages) : illustrations |
| Disciplina | 681/.2 |
| Soggetto topico |
Engineering mathematics - Data processing
Measurement - Data processing Estimation theory - Data processing |
| ISBN |
1-119-15245-3
1-119-15244-5 1-119-15248-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910811584503321 |
|
Heijden Ferdinand van der
|
||
| Hoboken, New Jersey : , : Wiley, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Classification, parameter estimation, and state estimation : an engineering approach using MATLAB / / F. van der Heijden ... [et al.]
| Classification, parameter estimation, and state estimation : an engineering approach using MATLAB / / F. van der Heijden ... [et al.] |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, West Sussex, Eng. ; ; Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (441 p.) |
| Disciplina | 681/.2 |
| Altri autori (Persone) | HeijdenFerdinand van der |
| Soggetto topico |
Engineering mathematics - Data processing
Measurement - Data processing Estimation theory - Data processing |
| ISBN |
1-280-26895-6
9786610268955 0-470-09015-4 1-60119-496-X 0-470-09014-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Classification, Parameter Estimation and State Estimation; Contents; Preface; Foreword; 1 Introduction; 1.1 The scope of the book; 1.1.1 Classification; 1.1.2 Parameter estimation; 1.1.3 State estimation; 1.1.4 Relations between the subjects; 1.2 Engineering; 1.3 The organization of the book; 1.4 References; 2 Detection and Classification; 2.1 Bayesian classification; 2.1.1 Uniform cost function and minimum error rate; 2.1.2 Normal distributed measurements; linear and quadratic classifiers; 2.2 Rejection; 2.2.1 Minimum error rate classification with reject option
2.3 Detection: the two-class case2.4 Selected bibliography; 2.5 Exercises; 3 Parameter Estimation; 3.1 Bayesian estimation; 3.1.1 MMSE estimation; 3.1.2 MAP estimation; 3.1.3 The Gaussian case with linear sensors; 3.1.4 Maximum likelihood estimation; 3.1.5 Unbiased linear MMSE estimation; 3.2 Performance of estimators; 3.2.1 Bias and covariance; 3.2.2 The error covariance of the unbiased linear MMSE estimator; 3.3 Data fitting; 3.3.1 Least squares fitting; 3.3.2 Fitting using a robust error norm; 3.3.3 Regression; 3.4 Overview of the family of estimators; 3.5 Selected bibliography 3.6 Exercises4 State Estimation; 4.1 A general framework for online estimation; 4.1.1 Models; 4.1.2 Optimal online estimation; 4.2 Continuous state variables; 4.2.1 Optimal online estimation in linear-Gaussian systems; 4.2.2 Suboptimal solutions for nonlinear systems; 4.2.3 Other filters for nonlinear systems; 4.3 Discrete state variables; 4.3.1 Hidden Markov models; 4.3.2 Online state estimation; 4.3.3 Offline state estimation; 4.4 Mixed states and the particle filter; 4.4.1 Importance sampling; 4.4.2 Resampling by selection; 4.4.3 The condensation algorithm; 4.5 Selected bibliography 4.6 Exercises5 Supervised Learning; 5.1 Training sets; 5.2 Parametric learning; 5.2.1 Gaussian distribution, mean unknown; 5.2.2 Gaussian distribution, covariance matrix unknown; 5.2.3 Gaussian distribution, mean and covariance matrix both unknown; 5.2.4 Estimation of the prior probabilities; 5.2.5 Binary measurements; 5.3 Nonparametric learning; 5.3.1 Parzen estimation and histogramming; 5.3.2 Nearest neighbour classification; 5.3.3 Linear discriminant functions; 5.3.4 The support vector classifier; 5.3.5 The feed-forward neural network; 5.4 Empirical evaluation; 5.5 References 5.6 Exercises6 Feature Extraction and Selection; 6.1 Criteria for selection and extraction; 6.1.1 Inter/intra class distance; 6.1.2 Chernoff-Bhattacharyya distance; 6.1.3 Other criteria; 6.2 Feature selection; 6.2.1 Branch-and-bound; 6.2.2 Suboptimal search; 6.2.3 Implementation issues; 6.3 Linear feature extraction; 6.3.1 Feature extraction based on the Bhattacharyya distance with Gaussian distributions; 6.3.2 Feature extraction based on inter/intra class distance; 6.4 References; 6.5 Exercises; 7 Unsupervised Learning; 7.1 Feature reduction; 7.1.1 Principal component analysis 7.1.2 Multi-dimensional scaling |
| Record Nr. | UNINA-9910877862403321 |
| Chichester, West Sussex, Eng. ; ; Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
