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Sooner or later, power system protection is going to cost money. How much is entirely up to you. Setting up a safe and effective AC power system from the very beginning can help avoid costly downtime and repairs, provide backup power during system outages, and minimize workplace accidents. For the past 15 years, Jerry Whitaker’s AC Power Systems Handbook has supplied industry professionals with a comprehensive, practical guide to the key elements of AC power for commercial and industrial systems.
This third edition is thoroughly revised and completely reorganized to reflect the changing demands of modern power systems. To ease navigation, many sections are now presented as separate chapters filled with updated and expanded information. Most notably, the author adds heavily in the areas of transient suppression hardware, electrical system components, and power system fundamentals. Following a logical progression, coverage flows from power system operation to protecting equipment loads, selecting the right level of protection, grounding, standby power, and safety. Along the way, the author paints a clear picture of the sources of disturbances, the tradeoffs involved for different options, and the advantages and limitations of various approaches.
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The effort to build machines that are able to learn and undertake tasks such as datamining, image processing and pattern recognition has led to the development of artificial neural networks in which learning from examples may be described and understood. The contribution to this subject made over the past decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics, and include many examples and exercises.
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Learning is one of the things that humans do naturally, and it has always been a challenge for us to understand the process. Nowadays this challenge has another dimension as we try to build machines that are able to learn and to undertake tasks such as datamining, image processing and pattern recognition. We can formulate a simple framework, artificial neural networks, in which learning from examples may be described and understood. The contribution to this subject made over the last decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics and include many examples and exercises to make a book that can be used with courses, or for self-teaching, or as a handy reference.
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This book is a collection of papers presented at the last Scientific Computing in Electrical Engineering (SCEE) Conference, held in Capo dOrlando, Sicily, in 2004.www.viewzoft.com. The series of SCEE conferences aims at addressing mathematical problems which have a relevancy to industry. The areas covered at SCEE-2004 were: Electromagnetism, Circuit Simulation, Coupled Problems and General mathematical and computational methods. This book is particularly important for Engineers, Physicists and Mathematicians who want to know the state of the art with respect to scientific challenges arising from problems of interest for industry.
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