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This book provides readers with an in-depth discussion of circuit simulation, combining basic electrical engineering circuit theory with Python programming. It fills an information gap by describing the development of Python Power Electronics, an open-source software for simulating circuits, and demonstrating its use in a sample circuit. Unlike typical books on circuit theory that describe how circuits can be solved mathematically, followed by examples of simulating circuits using specific, commercial software, this book has a different approach and focus. The author begins by describing every aspect of the open-source software, in the context of non-linear power electronic circuits, as a foundation for aspiring or practicing engineers to embark on further development of open source software for different purposes. By demonstrating explicitly the operation of the software through algorithms, this book brings together the fields of electrical engineering and software technology.
This is the second book in the Deep Learning models series by the author. Deep learning models are widely used in different fields due to its capability to handle large and complex datasets and produce the desired results with more accuracy at a greater speed. In Deep learning models, features are selected automatically through the iterative process wherein the model learns the features by going deep into the dataset and selects the features to be modeled. In the traditional models the features of the dataset needs to be specified in advance. The Deep Learning algorithms are derived from Artificial Neural Network concepts and it is a part of broader Machine Learning Models. The book starts with the Introduction part which is adopted from Author’s Deep Learning Models and its application: An overview with the help of R software book and move on to the Python’s important data processing packages such Numpy, and Pandas. Book then explores the Deep Learning models with the help of packages such as Pytorch, Tensor Flow and Keras and their applications in image processing, stock market prediction, recommender systems and natural language processing. Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php ISBN: 9798558877953 E-Books: https://www.amazon.com/dp/B08MQTM1ZP Paperbacks: https://www.amazon.com/dp/B08MSQ3R8R
Deep Learning Models and its application: An overview with the help of R softwarePrefaceDeep learning models are widely used in different fields due to its capability to handle large and complex datasets and produce the desired results with more accuracy at a greater speed. In Deep learning models, features are selected automatically through the iterative process wherein the model learns the features by going deep into the dataset and selects the features to be modeled. In the traditional models the features of the dataset needs to be specified in advance. The Deep Learning algorithms are derived from Artificial Neural Network concepts and it is a part of broader Machine Learning Models. This book intends to provide an overview of Deep Learning models, its application in the areas of image recognition & classification, sentiment analysis, natural language processing, stock market prediction using R statistical software package, an open source software package. The book also includes an introduction to python software package which is also open source software for the benefit of the users.This books is a second book in series after the author’s first book- Machine Learning: An Overview with the Help of R Software https://www.amazon.com/dp/B07KQSN447EditorInternational Journal of Statistics and Medical Informaticswww.ijsmi.com/book.php
This book describes the role of magnetism in electrical engineering, starting from the most basic laws of physics, converted into simulation models such that electrical engineering students can learn by example and practice. The author demystifies a topic that many electrical engineers take for granted, providing readers the tools to be able to understand how any magnetic component works. He describes magnetic components like inductors and transformers in simple understandable language. Mathematical equations related to the basic laws of physics are described in detail along with the physical significance of the equations. Every application is supported by a simulation. All simulations are performed using free and open source software based on Python making the material in this book universally accessible.
Covers advanced analyses and the creation of models and subcircuits. This book also includes coverage of transmission lines, the special elements which are used to connect components in PCBs and integrated circuits. Finally, it includes a description of Ultiboard, the tool for PCB creation from a circuit description in Multisim.
This book is an in-depth description on how to design digital filters. The presentation is geared for practicing engineers, using open source computational tools, while incorporating fundamental signal processing theory. The author includes theory as-needed, with an emphasis on translating to practical application. The book describes tools in detail that can be used for filter design, along with the steps needed to automate the entire process. Breaks down signal processing theory into simple, understandable language for practicing engineers; Provides readers with a highly-practical introduction to digital filter design; Uses open source computational tools, while incorporating fundamental signal processing theory; Describes examples of digital systems in engineering and a description of how they are implemented in practice; Includes case studies where filter design is described in depth from inception to final implementation.
This book shows readers how to learn analog electronics by simulating circuits. Readers will be enabled to master basic electric circuit analysis, as an essential component of their professional education. The author’s approach enables readers to learn theory as needed, then immediately apply it to the simulation of circuits based on that theory, while using the resulting tables, graphs and waveforms to gain a deeper insight into the theory, as well as where theory and practice diverge!
The use of MATLAB is ubiquitous in the scientific and engineering communities today, and justifiably so. Simple programming, rich graphic facilities, built-in functions, and extensive toolboxes offer users the power and flexibility they need to solve the complex analytical problems inherent in modern technologies. The ability to use MATLAB effectively has become practically a prerequisite to success for engineering professionals. Like its best-selling predecessor, Electronics and Circuit Analysis Using MATLAB, Second Edition helps build that proficiency. It provides an easy, practical introduction to MATLAB and clearly demonstrates its use in solving a wide range of electronics and circuit analysis problems. This edition reflects recent MATLAB enhancements, includes new material, and provides even more examples and exercises. New in the Second Edition: Thorough revisions to the first three chapters that incorporate additional MATLAB functions and bring the material up to date with recent changes to MATLAB A new chapter on electronic data analysis Many more exercises and solved examples New sections added to the chapters on two-port networks, Fourier analysis, and semiconductor physics MATLAB m-files available for download Whether you are a student or professional engineer or technician, Electronics and Circuit Analysis Using MATLAB, Second Edition will serve you well. It offers not only an outstanding introduction to MATLAB, but also forms a guide to using MATLAB for your specific purposes: to explore the characteristics of semiconductor devices and to design and analyze electrical and electronic circuits and systems.
Simulation of Power Electronics Converters Using PLECS® is a guide to simulating a power electronics circuit using the latest powerful software for power electronics circuit simulation purposes. This book assists engineers gain an increased understanding of circuit operation so they can, for a given set of specifications, choose a topology, select appropriate circuit component types and values, estimate circuit performance, and complete the design by ensuring that the circuit performance will meet specifications even with the anticipated variations in operating conditions and circuit component values. This book covers the fundamentals of power electronics converter simulation, along with an analysis of power electronics converters using PLECS. It concludes with real-world simulation examples for applied content, making this book useful for all those in the electrical and electronic engineering field. - Contains unique examples on the simulation of power electronics converters using PLECS® - Includes explanations and guidance on all included simulations for re-doing the simulations - Incorporates analysis and design for rapidly creating power electronics circuits with high accuracy
Modeling and Simulation in Python teaches readers how to analyze real-world scenarios using the Python programming language, requiring no more than a background in high school math. Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modeling—that is, the art of describing and simulating real-world systems. Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions. Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.