Introduction to Insulated Gate Bipolar Transistors Prepared by: Jack Takesuye and scott Deuty Motorola inc INTRODUCTION As power conversion relies more on switched applications The IGBT is, in fact, a spin-off from power MOSFET

Introduction Some basic concepts Basic step of statistical work Review questions and exercises

Introduction & Motivation Introduction & Motivation Model & Simulation Model & Simulation Results Results  Domain Patterns Domain Patterns  Energy Terms Energy Terms  Field Enhanced Piezoelectricity Field Enhanced Piezoelectricity  Enhanced Piezoelectricity at Zero Field Enhanced Piezoelectricity at Zero Field  Enhanced Piezoelectricity: Critical Phenomena Enhanced Piezoelectricity: Critical Phenomena Summary Summary

§1-1 General introduction §1-2 Discipiline of metal stamping 金属冲压变形规律 §1-3 Introduction of press tools 冲压模具概述

• Introduction • Supervised Learning – Convolutional Neural Network – Sequence Modelling: RNN and its extensions • Unsupervised Learning – Autoencoder – Stacked DenoisingAutoencoder • Reinforcement Learning – Deep Reinforcement Learning – Two applications: Playing Atari & AlphaGo

 Introduction  Context  Deixis, reference, anaphora  Speech Acts  Cooperative principle in conversations  Politeness

1. Introduction 2. Applications 3. Characteristics of Serial I/O 4. Characteristics of Parallel I/O 5. Introduction to MPI-2 Parallel I/O 6. MPI-2 File Structure 7. Initializing MPI-2 File I/O 8. Defining A View 9. Data Access - Reading Data 10.Data Access - Writing Data 11.Closing MPI-2 File I/O

INTRODUCTION EUROPEAN LEGAL HISTORY: COMMON LAW AND CIVIL LAW TRADITIONS DICHOTOMY PRIVATE LAW / PUBLIC LAW: CONSTRUCTION, DEVELOPMENT AND IMPLICATIONS PRIVATE LAW AN EUROPEAN UNIFICATION OF PRIVATE LAW? PUBLIC LAW

1.1 Introduction 1.2 Quantitative Features of Modern Economics 1.3 Mathematical Modeling 1.4 Empirical Validation 1.5 Illustrative Examples 1.6 Limitations of Econometric Analysis

• Introduction to ANNs – Taxonomy – Features – Learning – Applications • Supervised ANNs – Examples – Applications – Further topics • Unsupervised ANNs – Examples – Applications – Further topics