Probability and Random Variables for Electrical Engineering: Probability: Measurement of Uncertainty: 390 (Studies in Systems, Decision and Control) - Tapa blanda

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Muammer Catak, Ph.D., is working in College of Engineering and Technology, American University of the Middle East, Kuwait.

Muammer Catak is Faculty Member of Electrical Engineering Department at College of Engineering and Technology, American University of the Middle East, Kuwait. He received his B.Sc. in Electrical and Electronics Engineering from the Middle East Technical University, Turkey in 2004, the M.Sc. in Telecommunication and Signal Processing, Blekinge Technical Institute, Sweden in 2006, the Ph.D. in Stochastic Modelling and Simulation from Process Engineering, University College Cork, Ireland in 2010.  He got his Associate Professorship degree in the subject of Signal Processing / Electrical and Electronics Engineering, Turkey in 2017.    

His main research interests include stochastic signal processing, random processes, and Markov chains.  He published 19 scientific articles in various international peer-reviewed journals.  He is Author of the book titled Markov Chain Modelling of the Re-circulatory Fluidised Bed Granulation: Stochastic Processes published in 2016. 

Tofigh Allahviranloo, Ph.D., is Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey.

Tofigh Allahviranloo is Full Professor of applied mathematics at Bahcesehir University, Turkey. As a trained mathematician and computer scientist, Prof. Allahviranloo has developed a passion for multi- and interdisciplinary research.

He is not only deeply involved in fundamental research in fuzzy applied mathematics, especially fuzzy differential equations, but he also aims at innovative applications in the applied biological sciences. He is Author of several books and many papers published by Elsevier and Springer. He actively serves the research community, as Editor-in-Chief of the International J. of Industrial Mathematics and Associate Editor of editorial board of several other journals, including Information Sciences, Fuzzy Sets and Systems, Journal of Intelligent and Fuzzy Systems, Iranian J. of Fuzzy systems, and Mathematical Sciences. 

Witold Pedrycz, Ph.D., is working in Department of Electrical and Computer Engineering, University of Alberta, Canada.

Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. In 2012, he was elected as Fellow of the Royal Society of Canada.

In 2007, he received a prestigious Norbert Wiener Award from the IEEE Systems, Man, and Cybernetics Society. He is a recipient of the IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, and a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society.

His main research directions involve computational intelligence, fuzzy modeling and granular computing, knowledge discovery and data science, pattern recognition, data science, knowledge-based neural networks, and control engineering. He is also Author of 18 research monographs and edited volumes covering various aspects of computational intelligence, data mining, and software engineering.

Dr. Pedrycz is vigorously involved in editorial activities. He is Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery, and Co-Editor-in-Chief of Int. J. of Granular Computing, and J. of Data Information and Management.  He serves on the Advisory Board of IEEE Transactions on Fuzzy Systems.

De la contraportada

This book delivers a concise and carefully structured introduction to probability and random variables. It aims to build a linkage between the theoretical conceptual topics and the practical applications, especially in the undergraduate engineering area. The book motivates the student to gain full understanding of the fundamentals of probability theory and help acquire working problem-solving skills and apply the theory to engineering applications. Each chapter includes solved examples at varying levels (both introductory and advanced) in addition to problems that demonstrate the relevance of the probability and random variables in engineering. As authors, we focused on to find out the optimum ways in order to introduce the topics in probability and random variables area.