Probability||Random Variables and Stochastic Processes

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Probability, Random Variables and Stochastic Processes is a reference book written with an intention to help the students in electrical engineering, physical departments, and math. It is intended to be used for a graduate/senior level course in probability. This is 4th edition of the book and has been updated, catering to the needs of the present students. This edition includes the intelligence and knowledge of S. Unnikrishna Pillai who is the co-author. The author takes a different approach in this book to reach to his readers. He intends to enhance the levels of probability theory as a deductive course of study. The book also illustrates the theoretical aspect with general applications of subjects in engineering. Though the style remains the same as that of the previous editions, almost one-third of the content is new. Moreover, this new edition contains supplementary examples to further shed light on the subject. Several new topics have been added in this latest edition to cover the gap between applications and concepts. The additional key features a new section on parameter estimation, random walks, and Markov Chains and queuing theory. Lastly, it incorporates a brand new design, offering easy accessibility to the readers to locate theorems and examples. Athanasios Papoulis, born in Greece in 1921, is a well-known Greek-American engineer and applied mathematician. His written works cover various topics of engineering mathematics such as statistics and probability. His books emphasize the physical and engineering interpretations of probability instead of just focusing on mathematical rigor. Some of his books include Systems and Transforms With Applications in Optics, Probability and Statistics, and Circuits and Systems: A Modern Approach (H R W Series in Electrical and Computer Engineering).He graduated from the National Technical University of Athens. S. Unnikrishna Pillai is working as a professor in the Department of Electrical Engineering in Polytechnic University, Brooklyn. His other major works include Waveform Diversity: Theory & Applications. He did his Ph.D. in Array Signal Processing and Spectrum Estimation from University of Pennsylvania.