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A First Course in Statistics for Signal Analysis

Posted By: AvaxGenius
A First Course in Statistics for Signal Analysis

A First Course in Statistics for Signal Analysis by Wojbor A. Woyczynski
English | PDF(True) | 2011 | 271 Pages | ISBN : 0817681000 | 4.9 MB

'A First Course in Statistics for Signal Analysis' is a small, dense, and inexpensive book that covers exactly what the title says: statistics for signal analysis. The book has much to recommend it. The author clearly understands the topics presented. The topics are covered in a rigorous manner, but not so rigorous as to be ostentatious. The sequence of topics is clearly targeted at the spectral properties of Gaussian stationary signals. Any student studying traditional communications and signal processing would benefit from an understanding of these topics…In summary, [the work] has much in its favor…This book is most appropriate for a graduate class in signal analysis. It also could be used as a secondary text in a statistics, signal processing, or communications class.

Basic Stochastic Processes: A Course Through Exercises (Repost)

Posted By: AvaxGenius
Basic Stochastic Processes: A Course Through Exercises (Repost)

Basic Stochastic Processes: A Course Through Exercises By Zdzisław Brzeźniak
English | PDF,EPUB | 1999 | 229 Pages | ISBN : 3540761756 | 18.2 MB

This book has been designed for a final year undergraduate course in stochastic processes. It will also be suitable for mathematics undergraduates and others with interest in probability and stochastic processes, who wish to study on their own. The main prerequisite is probability theory: probability measures, random variables, expectation, independence, conditional probability, and the laws of large numbers. The only other prerequisite is calculus.

Probability and Simulation

Posted By: AvaxGenius
Probability and Simulation

Probability and Simulation by Giray Ökten
English | PDF,EPUB | 2020 | 158 Pages | ISBN : 3030560694 | 18 MB

This undergraduate textbook presents an inquiry-based learning course in stochastic models and computing designed to serve as a first course in probability. Its modular structure complements a traditional lecture format, introducing new topics chapter by chapter with accompanying projects for group collaboration.