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This graduate text covers a variety of mathematical and statistical tools for the analysis of big data coming from biology, medicine and economics. Neural networks, Markov chains, tools from statistical physics and wavelet analysis are used to develop efficient computational algorithms, which are then used for the processing of real-life data using Matlab.

Bioinformatik. --- Datenanalyse. --- Maschinelles Lernen. --- Massendaten. --- Ökonometrie.

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Robustly maintaining balance on two legs is an important challenge for humanoid robots. The work presented in this book represents a contribution to this area. It investigates efficient methods for the decision-making from internal sensors about whether and where to step, several improvements to efficient whole-body postural balancing methods, and proposes and evaluates a novel method for efficient recovery step generation, leveraging human examples and simulation-based reinforcement learning.

Maschinelles Lernen --- Balancing --- Optimierung --- Regelungstechnik --- Machine learning --- Balancieren --- Control systems --- Humanoide Robotik --- Humanoid robotics --- Optimization

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This book describes the development of a new method for personalisation of efficiency factors in partial body counting. Its achieved goal is the quantification of uncertainties in those factors due to variation in anatomy of the measured persons, and their reduction by correlation with anthropometric parameters. The method was applied to a detector system at the In Vivo Measurement Laboratory at Karlsruhe Institute of Technology using Monte Carlo simulation and computational phantoms.

Computational phantom --- Maschinelles Lernen --- Anthropometry --- Partial body counter --- Efficiency calibration --- Machine learning --- Teilkörperzähler --- Computerphantom --- Effizienzkalibrierung --- Anthropometrie

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Automated visual inspection is an integral part in industrial manufacturing processes, but development and setup of such systems is very costly. Machine learning significantly reduces the effort of and speeds up both tasks. This work develops several machine learning methods suitable for automated visual inspection. The methods augment each other and can be used for a wide range of products.

Mustererkennung --- Schüttgutsortierung --- visual inspection --- optische Inspektion --- maschinelles Lernen --- Pattern recognition --- machine learning --- bulk material soriting

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The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.

Vorhofflimmern --- Fibrose --- maschinelles Lernen --- Bidomain --- Modellierung des Herzens --- atrial fibrillation --- fibrosis --- machine learning --- bidomain --- cardiac modeling