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|z (OCoLC)1132293716
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|2 23
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|a Langer, Horst.
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|a Advantages and Pitfalls of Pattern Recognition :
|b Selected Cases in Geophysics /
|c Horst Langer, Susanna Falsaperla, Conny Hammer.
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| 260 |
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|a San Diego :
|b Elsevier,
|c 2020.
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|a 1 online resource (352 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Computational geophysics series ;
|v v. 3
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| 588 |
0 |
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|a Print version record.
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|a Front Cover; Advantages and Pitfalls of Pattern Recognition; Advantages and Pitfalls of Pattern Recognition; Copyright; Contents; Preface; Acknowledgments; I -- From data to methods; 1 -- Patterns, objects, and features; 1.1 Objects and patterns; 1.2 Features; 1.2.1 Types; 1.2.2 Feature vectors; 1.2.3 Feature extraction; 1.2.3.1 Delineating segments; 1.2.3.2 Delineating regions; 1.2.4 Transformations; 1.2.4.1 Karhunen-Lo�eve transformation (Principal Component Analysis); 1.2.4.2 Independent Component Analysis; 1.2.4.3 Fourier transform; 1.2.4.4 Short-time Fourier transform and spectrograms
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| 505 |
8 |
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|a 1.2.4.5 Discrete wavelet transforms1.2.5 Standardization, normalization, and other preprocessing steps; 1.2.5.1 Comments; 1.2.5.2 Outlier removal; 1.2.5.3 Missing data; 1.2.6 Curse of dimensionality; 1.2.7 Feature selection; Appendix 1 Basic notions on statistics; A1.1 Statistical parameters of an ensemble; A1.2 Distinction of ensembles; 2 -- Supervised learning; 2.1 Introduction; 2.2 Discriminant analysis; 2.2.1 Test ban treaty-some history; 2.2.2 The MS-mb criterion for nuclear test identification; 2.2.3 Linear Discriminant Analysis; 2.3 The linear perceptron
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|a 2.4 Solving the XOR problem: classification using multilayer perceptrons (MLPs)2.4.1 Nonlinear perceptrons; 2.5 Support vector machines (SVMs); 2.5.1 Linear SVM; 2.5.2 Nonlinear SVM, kernels; 2.6 Hidden Markov Models (HMMs)/sequential data; 2.6.1 Background-from patterns and classes to sequences and processes; 2.6.2 The three problems of HMMs; 2.6.3 Including prior knowledge/model dimensions and topology; 2.6.4 Extension to conditional random fields; 2.7 Bayesian networks; Appendix 2; Appendix 2.1 Fisher's linear discriminant analysis; Appendix 2.2 The perceptron; Backpropagation
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|a Appendix 2.3 SVM optimization of the marginsAppendix 2.4. Hidden Markov models; Appendix 2.4.1. Evaluation; Appendix 2.4.2. Decoding-the Viterbi algorithm; Appendix 2.4.3. Training-the expectation-maximization /Baum-Welch algorithm; 3 -- Unsupervised learning; 3.1 Introduction; 3.1.1 Metrics of (dis)similarity; 3.1.2 Clustering; 3.1.2.1 Partitioning clustering; 3.1.2.1.1 Fuzzy clustering; 3.1.2.2 Hierarchical clustering; 3.1.2.3 Density-based clustering; 3.2 Self-Organizing Maps; 3.2.1 Training of an SOM; Appendix 3; Appendix 3.1. Analysis of variance (ANOVA)
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|a Appendix 3.2 Minimum distance property for the determinant criterionAppendix 3.3. SOM quality; Topological error; Designing the map; II -- Example applications; 4 -- Applications of supervised learning; 4.1 Introduction; 4.2 Classification of seismic waveforms recorded on volcanoes; 4.2.1 Signal classification of explosion quakes at Stromboli; 4.2.2 Cross-validation issues; 4.3 Infrasound classification; 4.3.1 Infrasound monitoring at Mt Etna-classification with SVM; 4.4 SVM classification of rocks; 4.5 Inversion with MLP; 4.5.1 Identification of parameters governing seismic waveforms
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| 500 |
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|a 4.5.2 Integrated inversion of geophysical data
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| 650 |
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0 |
|a Geophysics
|x Data processing.
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| 650 |
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0 |
|a Pattern perception.
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| 650 |
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6 |
|a G�eophysique
|x Informatique.
|0 (CaQQLa)201-0382101
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| 650 |
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6 |
|a Perception des structures.
|0 (CaQQLa)201-0027390
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| 650 |
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7 |
|a Geophysics
|x Data processing
|2 fast
|0 (OCoLC)fst00941009
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| 650 |
|
7 |
|a Pattern perception
|2 fast
|0 (OCoLC)fst01055254
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| 700 |
1 |
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|a Falsaperla, Susanna.
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| 700 |
1 |
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|a Hammer, Conny.
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| 776 |
0 |
8 |
|i Print version:
|a Langer, Horst.
|t Advantages and Pitfalls of Pattern Recognition : Selected Cases in Geophysics.
|d San Diego : Elsevier, �2019
|z 9780128118429
|
| 830 |
|
0 |
|a Computational geophysics series ;
|v v. 3.
|
| 856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128118429
|z Texto completo
|
