Introduction To Applied Statistical Signal Analysis
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Introduction To Applied Statistical Signal Analysis
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Author : Richard Shiavi
language : en
Publisher: Elsevier
Release Date : 2010-07-19
Introduction To Applied Statistical Signal Analysis written by Richard Shiavi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-19 with Technology & Engineering categories.
Introduction to Applied Statistical Signal Analysis, Third Edition, is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech. Topics presented include mathematical bases, requirements for estimation, and detailed quantitative examples for implementing techniques for classical signal analysis. This book includes over one hundred worked problems and real world applications. Many of the examples and exercises use measured signals, most of which are from the biomedical domain. The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically. Includes over one hundred worked problems and real world applications. Many of the examples and exercises in the book use measured signals, many from the biomedical domain.
Introduction To Applied Statistical Signal Analysis
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Author : Richard Shiavi
language : en
Publisher:
Release Date : 1999
Introduction To Applied Statistical Signal Analysis written by Richard Shiavi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Medical categories.
The enclosed CD-ROM provides a mode of learning that is interactive and suited for self-pacing and independent learning."--BOOK JACKET.
An Introduction To Statistical Signal Processing
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Author : Robert M. Gray
language : en
Publisher: Cambridge University Press
Release Date : 2004-12-02
An Introduction To Statistical Signal Processing written by Robert M. Gray and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-02 with Technology & Engineering categories.
This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.
Introduction To Statistical Signal Processing With Applications 1 E
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Author : Mandyam Dhati Srinath
language : en
Publisher:
Release Date : 1979
Introduction To Statistical Signal Processing With Applications 1 E written by Mandyam Dhati Srinath and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Estimation theory categories.
A First Course In Statistics For Signal Analysis
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Author : Wojbor A. Woyczynski
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-26
A First Course In Statistics For Signal Analysis written by Wojbor A. Woyczynski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-26 with Mathematics categories.
This self-contained, deliberately compact, and user-friendly book is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, explained in a concise, yet fairly rigorous presentation. Developed by the author over the course of several years of classroom use, this book may be used by junior/senior undergraduates or graduate students in electrical, systems, computer, and biomedical engineering, as well as the physical sciences.
Introduction To Statistical Signal Processing With Applications
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Author : Mandyam D. Srinath
language : en
Publisher:
Release Date : 1999
Introduction To Statistical Signal Processing With Applications written by Mandyam D. Srinath and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.
A First Course In Statistics For Signal Analysis
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Author : Wojbor A. Woyczyński
language : en
Publisher: Springer Nature
Release Date : 2019-10-04
A First Course In Statistics For Signal Analysis written by Wojbor A. Woyczyński and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-04 with Mathematics categories.
This self-contained and user-friendly textbook is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, which are explained in a concise, yet rigorous presentation. With abundant practice exercises and thorough explanations, A First Course in Statistics for Signal Analysis is an excellent tool for both teaching students and training laboratory scientists and engineers. Improvements in the second edition include considerably expanded sections, enhanced precision, and more illustrative figures.
Statistical Signal Processing
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Author : Swagata Nandi
language : en
Publisher: Springer Nature
Release Date : 2020-08-21
Statistical Signal Processing written by Swagata Nandi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-21 with Computers categories.
This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics.
Digital And Statistical Signal Processing
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Author : Anastasia Veloni
language : en
Publisher: CRC Press
Release Date : 2018-10-03
Digital And Statistical Signal Processing written by Anastasia Veloni and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Technology & Engineering categories.
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.
Statistical Signal Processing For Neuroscience And Neurotechnology
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Author : Karim G. Oweiss
language : en
Publisher: Academic Press
Release Date : 2010-09-22
Statistical Signal Processing For Neuroscience And Neurotechnology written by Karim G. Oweiss and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-22 with Science categories.
This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems. Written by experts in the field, the book is an ideal reference for researchers working in the field of neural engineering, neural interface, computational neuroscience, neuroinformatics, neuropsychology and neural physiology. By giving a broad overview of the basic principles, theories and methods, it is also an ideal introduction to statistical signal processing in neuroscience. A comprehensive overview of the specific problems in neuroscience that require application of existing and development of new theory, techniques, and technology by the signal processing community Contains state-of-the-art signal processing, information theory, and machine learning algorithms and techniques for neuroscience research Presents quantitative and information-driven science that has been, or can be, applied to basic and translational neuroscience problems