This book is based on my Master's in Engineering thesis.

Explores methods of fault identification through programming and simulation in MATLAB Examines signal processing tools and their applications with examples Provides knowledge of artificial neural networks and their applications with illustrations Uses PNN and BPNN to identify the different types of faults and obtain their corresponding locations Discusses the programming of signal processing using Wavelet Transform and S-Transform

Power System Fault Diagnosis: A Wide Area Measurement Based Intelligent Approach is a comprehensive overview of the growing interests in efficient diagnosis of power system faults to reduce outage duration and revenue losses by expediting the restoration process.This book illustrates intelligent fault diagnosis schemes for power system networks, at both transmission and distribution levels, using data acquired from phasor measurement units. It presents the power grid modeling, fault modeling, feature extraction processes, and various fault diagnosis techniques, including artificial intelligence techniques, in steps. The book also incorporates uncertainty associated with line parameters, fault information (resistance and inception angle), load demand, renewable energy generation, and measurement noises. - Provides step-by-step modeling of power system networks (distribution and transmission) and faults in MATLAB/SIMULINK and real-time digital simulator (RTDS) platforms - Presents feature extraction processes using advanced signal processing techniques (discrete wavelet and Stockwell transforms) and an easy-to-understand optimal feature selection method - Illustrates comprehensive results in the graphical and tabular formats that can be easily reproduced by beginners - Highlights various utility practices for fault location in transmission networks, distribution systems, and underground cables.

This book explores the use of wavelet transforms in signal processing, including image, finance, and communication systems. It covers five contemporary applications, including the interaction between inertial sensors and wavelet filtering techniques, geophysical prospecting, volatility patterns in asset returns, computerized tomography (CT), and fault detection techniques. The book provides a foundation for further exploration, focusing on wavelet transformations' basic principles, their application in geophysical prospecting, and their use in identifying volatility patterns in asset returns. The book is intended for students, researchers, and professionals interested in understanding wavelet transforms and their practical implementations.

An original reference applying wavelet analysis to power systems engineering • Introduces a modern signal processing method called wavelet analysis, and more importantly, its applications to power system fault detection and protection • Concentrates on its application to the power system, offering great potential for fault detection and protection • Presents applications, examples, and case studies, together with the latest research findings • Provides a combination of the author’s tutorial notes from electrical engineering courses together with his own original research work, of interest to both industry and academia

Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.

Wavelet Transform and Complexity presents high-level content on the fascinating field of wavelet transform and its applications in real-world phenomena. Divided into two parts, Analysis and Real-World Applications, the book describes the application of the wavelet method to several interesting complex systems across various disciplines. The book is designed for students, postdocs, and researchers interested in studying the wavelet method and its applications.