This book Electric Circuit Analysis attempts to provide an exhaustive treatment of the basic foundations and principles of circuit analysis, which should become an integral part of a students knowledge in his pursuit of the study of further topics in electrical engineering. The topics covered can be handled quite comfortably in two academic semesters. Numerous solved problems are provided to illustrate the concepts. In addition, a large number of exercise problems have been included at the end of each chapter. This revised edition covers some additional topics separately in an appendix. Further, some revisions and corrections have been incorporated in the text, as per the suggestions given by teachers and students of electrical engineering. The book draws upon three decades of teaching experience of the author in this subject. Students are advised to work out the problems and enhance their learning and knowledge of the subject. The book includes objective type questions to help students prepare for competitive examinations.
Problems And Solutions In Electric Circuit Analysis provides an extensive approach to problem solving in the basic principles of circuit analysis. It is a knowledge-based book that will help the reader to pursue further study in this discipline. The solutions to the problems are well-balanced for polytechnic colleges, engineering colleges and university level studies.There are seventeen chapters in the book. The topics included can be covered in two academic semesters. The main objective of the book is to enable the students to clearly understand the method of solving electric circuit problems.
This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.
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