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Author Langer, Horst.

Title Advantages and Pitfalls of Pattern Recognition : Selected Cases in Geophysics / Horst Langer, Susanna Falsaperla, Conny Hammer.

Imprint San Diego : Elsevier, 2020.

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Location Call No. OPAC Message Status
 Axe Elsevier ScienceDirect Ebook  Electronic Book    ---  Available
Description 1 online resource (352 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series Computational geophysics series ; v. 3
Computational geophysics series ; v. 3.
Note Print version record.
Contents 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-Loève 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
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
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
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)
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
Note 4.5.2 Integrated inversion of geophysical data
Subject Geophysics -- Data processing.
Pattern perception.
Géophysique -- Informatique.
Perception des structures.
Geophysics -- Data processing
Pattern perception
Added Author Falsaperla, Susanna.
Hammer, Conny.
Other Form: Print version: Langer, Horst. Advantages and Pitfalls of Pattern Recognition : Selected Cases in Geophysics. San Diego : Elsevier, ©2019 9780128118429
ISBN 9780128118436
0128118431
9780128118429 (pbk.)
Standard No. AU@ 000066421730
UKMGB 019616661

 
    
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