Digital and Statistical Signal Processing

Digital and Statistical Signal Processing

Digital and Statistical Signal Processing

Digital and Statistical Signal Processing

eBook

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Overview

Nowadays, many aspects of electrical and electronic engineering are essentially applications of DSP. This is due to the focus on processing information in the form of digital signals, using certain DSP hardware designed to execute software. Fundamental topics in digital signal processing are introduced with theory, analytical tables, and applications with simulation tools. The book provides a collection of solved problems on digital signal processing and statistical signal processing. The solutions are based directly on the math-formulas given in extensive tables throughout the book, so the reader can solve practical problems on signal processing quickly and efficiently.

FEATURES

  • Explains how applications of DSP can be implemented in certain programming environments designed for real time systems, ex. biomedical signal analysis and medical image processing.
  • Pairs theory with basic concepts and supporting analytical tables.
  • Includes an extensive collection of solved problems throughout the text.
  • Fosters the ability to solve practical problems on signal processing without focusing on extended theory.
  • Covers the modeling process and addresses broader fundamental issues.

  • Product Details

    ISBN-13: 9780429017575
    Publisher: CRC Press
    Publication date: 10/03/2018
    Sold by: Barnes & Noble
    Format: eBook
    Pages: 576
    File size: 18 MB
    Note: This product may take a few minutes to download.

    About the Author

    Professor Anastasia Veloni is with Piraeus University of Applied Sciences, Department of Computer Systems Engineering, Athens, Greece. She has extensive teaching experience in a variety of courses on the Automatic Control area and is author/co-author of four textbooks, while her research interests lie in the areas of signal processing and automatic control.

    Nikolaos I. Miridakis received his M.Sc. and Ph.D. degrees in Networking and Data Communications from the Department of Information Systems, Kingston University, U.K. in 2008 and from the Department of Informatics, University of Piraeus, Greece in 2012, respectively. Since 2007, he has been with the Department of Computer Systems Engineering, Piraeus University of Applied Sciences, Greece where he is an Adjunct Lecturer and Research Associate. Also, since 2012, he has been with the Department of Informatics, University of Piraeus, Greece where he is a Senior Research Associate. His research interests include wireless communications, and more specifically interference analysis and management in wireless communications, multicarrier communications, MIMO systems, statistical signal processing, diversity reception, fading channels, and cooperative communications.

    Dr. Erysso Boukouvala holds a BSc in Physics from the Department of Physics, University of Athens, an MSc in Applied Optics with a distinction and a PhD in the field of Digital Image Restoration from the Department of Physics, University of Reading, U.K. She works at the Department of Mathematics and Physics at the Hellenic Air Force Academy as a member of the Laboratory Teaching Staff. Since 2005, she has also been employed as a Teaching Fellow at the Department of Computer Systems Engineering, at Piraeus University of Applied Sciences, Athens. She has a wide teaching and lab experience in a variety of courses such as Digital Signal Processing, Applied Optics, Optoelectronics, Lasers, and Mechanics. She has participated in research projects in U.K. Her research focuses on the development of Digital Image Restoration techniques.

    Table of Contents

    Part 1: Digital Signal Processing. Introduction. Discrete-time Signals and Systems. z-Transform. Implementation of Discrete Systems. Frequency Domain Analysis. Designing Digital Filters. Part 2: Statistical Signal Processing. Statistical Models. Fundamental Principles of Parametric Estimation. Linear Evaluation. Fundamentals of Signal Detection.

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