November 26, 2020

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Introduction to Applied Statistical Signal Analysis

Introduction to Applied Statistical Signal Analysis
Author : Richard Shiavi
Publisher : Elsevier
Release Date : 2010-07-19
Category : Technology & Engineering
Total pages :424
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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

Introduction to Applied Statistical Signal Analysis
Author : Richard Shiavi
Publisher : Unknown
Release Date : 1999
Category : Mathematics
Total pages :390
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This book provides a balanced perspective of the concept, mathematical bases, requirements for estimation, and detailed quantitative examples of the implementation of the techniques for classical signal analysis. The presentation integrates theory and implementation, practical examples, homework exercises which range from pencil and paper format to computer-based format problems, to instructional notebooks. The notebooks provide a mode of learning that is interactive and suited for self-pacing and independent learning. * "real-world" applications * real data available for exercises and projects * notebooks for interactive learning * graphical explanation of concepts * exercises emphasizing concepts * CD-ROM with MATLAB implementation

An Introduction to Statistical Signal Processing

An Introduction to Statistical Signal Processing
Author : Robert M. Gray,Lee D. Davisson
Publisher : Cambridge University Press
Release Date : 2004-12-02
Category : Technology & Engineering
Total pages :129
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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.

Statistical Signal Processing for Neuroscience and Neurotechnology

Statistical Signal Processing for Neuroscience and Neurotechnology
Author : Karim G. Oweiss
Publisher : Academic Press
Release Date : 2010-09-22
Category : Science
Total pages :433
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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

Digital and Statistical Signal Processing

Digital and Statistical Signal Processing
Author : Anastasia Veloni,Nikolaos Miridakis,Erysso Boukouvala
Publisher : CRC Press
Release Date : 2018-10-03
Category : Technology & Engineering
Total pages :558
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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.

Fractional Order Signal Processing

Fractional Order Signal Processing
Author : Saptarshi Das,Indranil Pan
Publisher : Springer Science & Business Media
Release Date : 2011-09-15
Category : Mathematics
Total pages :101
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The book tries to briefly introduce the diverse literatures in the field of fractional order signal processing which is becoming an emerging topic among an interdisciplinary community of researchers. This book is aimed at postgraduate and beginning level research scholars who would like to work in the field of Fractional Order Signal processing (FOSP). The readers should have preliminary knowledge about basic signal processing techniques. Prerequisite knowledge of fractional calculus is not essential and is exposited at relevant places in connection to the appropriate signal processing topics. Basic signal processing techniques like filtering, estimation, system identification, etc. in the light of fractional order calculus are presented along with relevant application areas. The readers can easily extend these concepts to varied disciplines like image or speech processing, pattern recognition, time series forecasting, financial data analysis and modeling, traffic modeling in communication channels, optics, biomedical signal processing, electrochemical applications and many more. Adequate references are provided in each category so that the researchers can delve deeper into each area and broaden their horizon of understanding. Available MATLAB tools to simulate FOSP theories are also introduced so that the readers can apply the theoretical concepts right-away and gain practical insight in the specific domain.

Statistical Signal Processing

Statistical Signal Processing
Author : Debasis Kundu,Swagata Nandi
Publisher : Springer Science & Business Media
Release Date : 2012-05-24
Category : Computers
Total pages :132
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Signal processing may broadly be considered to involve the recovery of information from physical observations. The received signal is usually disturbed by thermal, electrical, atmospheric or intentional interferences. Due to the random nature of the signal, statistical techniques play an important role in analyzing the signal. Statistics is also used in the formulation of the appropriate models to describe the behavior of the system, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Statistical signal processing basically refers to the analysis of random signals using appropriate statistical techniques. The main aim of this book is to introduce different signal processing models which have been used in analyzing periodic data, and different statistical and computational issues involved in solving them. We discuss in detail the sinusoidal frequency model which has been used extensively in analyzing periodic data occuring in various fields. We have tried to introduce different associated models and higher dimensional statistical signal processing models which have been further discussed in the literature. Different real data sets have been analyzed to illustrate how different models can be used in practice. Several open problems have been indicated for future research.

Higher-order Statistical Signal Processing

Higher-order Statistical Signal Processing
Author : Boualem Boashash
Publisher : Unknown
Release Date : 1995
Category : Signal processing
Total pages :531
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Higher-Order Statistical Signal Processing brings together some most recent innovations in the field of higher-order statistical signal processing. It is structured to provide a comprehensive understanding of the fundamentals of the discipline, as well as a treatment of recent advances.

A First Course in Statistics for Signal Analysis

A First Course in Statistics for Signal Analysis
Author : Wojbor A. Woyczyński
Publisher : Springer Nature
Release Date : 2019-10-04
Category : Mathematics
Total pages :332
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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.

Discrete Random Signal Processing and Filtering Primer with MATLAB

Discrete Random Signal Processing and Filtering Primer with MATLAB
Author : Alexander D. Poularikas
Publisher : CRC Press
Release Date : 2018-10-03
Category : Technology & Engineering
Total pages :300
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Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering. Numerous Useful Examples, Problems, and Solutions – An Extensive and Powerful Review Written for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offers a solid review of recent developments in discrete signal processing. The book also details the latest progress in the revolutionary MATLAB language. A Practical Self-Tutorial That Transcends Theory The author introduces an incremental discussion of signal processing and filtering, and presents several new methods that can be used for a more dynamic analysis of random digital signals with both linear and non-linear filtering. Ideal as a self-tutorial, this book includes numerous examples and functions, which can be used to select parameters, perform simulations, and analyze results. This concise guide encourages readers to use MATLAB functions – and those new ones introduced as Book MATLAB Functions – to substitute many different combinations of parameters, giving them a firm grasp of how much each parameter affects results. Much more than a simple review of theory, this book emphasizes problem solving and result analysis, enabling readers to take a hands-on approach to advance their own understanding of MATLAB and the way it is used within signal processing and filtering.

Biosignal and Medical Image Processing, Third Edition

Biosignal and Medical Image Processing, Third Edition
Author : John L. Semmlow,Benjamin Griffel
Publisher : CRC Press
Release Date : 2014-02-25
Category : Medical
Total pages :630
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Written specifically for biomedical engineers, Biosignal and Medical Image Processing, Third Edition provides a complete set of signal and image processing tools, including diagnostic decision-making tools, and classification methods. Thoroughly revised and updated, it supplies important new material on nonlinear methods for describing and classifying signals, including entropy-based methods and scaling methods. A full set of PowerPoint slides covering the material in each chapter and problem solutions is available to instructors for download. See What’s New in the Third Edition: Two new chapters on nonlinear methods for describing and classifying signals. Additional examples with biological data such as EEG, ECG, respiration and heart rate variability Nearly double the number of end-of-chapter problems MATLAB® incorporated throughout the text Data "cleaning" methods commonly used in such areas as heart rate variability studies The text provides a general understanding of image processing sufficient to allow intelligent application of the concepts, including a description of the underlying mathematical principals when needed. Throughout this textbook, signal and image processing concepts are implemented using the MATLAB® software package and several of its toolboxes. The challenge of covering a broad range of topics at a useful, working depth is motivated by current trends in biomedical engineering education, particularly at the graduate level where a comprehensive education must be attained with a minimum number of courses. This has led to the development of "core" courses to be taken by all students. This text was written for just such a core course. It is also suitable for an upper-level undergraduate course and would also be of value for students in other disciplines that would benefit from a working knowledge of signal and image processing.

Statistical Signal Processing

Statistical Signal Processing
Author : T. Chonavel
Publisher : Springer Science & Business Media
Release Date : 2012-12-06
Category : Technology & Engineering
Total pages :331
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The only book on the subject at this level, this is a well written formalised and concise presentation of the basis of statistical signal processing. It teaches a wide variety of techniques, demonstrating how they can be applied to many different situations.

Signal Analysis and Prediction

Signal Analysis and Prediction
Author : Ales Prochazka,Nicholas Kingsbury,P.J.W. Payner,J. Uhlir
Publisher : Springer Science & Business Media
Release Date : 1998-12-23
Category : Technology & Engineering
Total pages :502
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Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book incorporates a collection of research papers based upon selected contri butions presented at the First European Conference on Signal Analysis and Predic tion (ECSAP-97) in Prague, Czech Republic, held June 24-27, 1997 at the Strahov Monastery. Even though the Conference was intended as a European Conference, at first initiated by the European Association for Signal Processing (EURASIP), it was very gratifying that it also drew significant support from other important scientific societies, including the lEE, Signal Processing Society of IEEE, and the Acoustical Society of America. The organizing committee was pleased that the re sponse from the academic community to participate at this Conference was very large; 128 summaries written by 242 authors from 36 countries were received. In addition, the Conference qualified under the Continuing Professional Development Scheme to provide PD units for participants and contributors.

Nonlinear Signal Processing

Nonlinear Signal Processing
Author : Gonzalo R. Arce
Publisher : John Wiley & Sons
Release Date : 2005-01-03
Category : Science
Total pages :480
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Nonlinear Signal Processing: A Statistical Approach focuses onunifying the study of a broad and important class of nonlinearsignal processing algorithms which emerge from statisticalestimation principles, and where the underlying signals arenon-Gaussian, rather than Gaussian, processes. Notably, byconcentrating on just two non-Gaussian models, a large set of toolsis developed that encompass a large portion of the nonlinear signalprocessing tools proposed in the literature over the past severaldecades. Key features include: * Numerous problems at the end of each chapter to aid developmentand understanding * Examples and case studies provided throughout the book in a widerange of applications bring the text to life and place the theoryinto context * A set of 60+ MATLAB software m-files allowing the reader toquickly design and apply any of the nonlinear signal processingalgorithms described in the book to an application of interest isavailable on the accompanying FTP site.

Robust Statistics for Signal Processing

Robust Statistics for Signal Processing
Author : Abdelhak M. Zoubir,Visa Koivunen,Esa Ollila,Michael Muma
Publisher : Cambridge University Press
Release Date : 2018-10-31
Category : Mathematics
Total pages :250
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Understand the benefits of robust statistics for signal processing using this unique and authoritative text.