Introduction to Applied Statistical Signal Analysis

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.

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  • Author : Richard Shiavi
  • Publisher : Elsevier
  • Pages : 424 pages
  • ISBN : 0080467687
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKIntroduction to Applied Statistical Signal Analysis

Introduction to Applied Statistical Signal Analysis

Introduction to Applied Statistical Signal Analysis
  • Author : Richard Shiavi
  • Publisher : Elsevier
  • Release : 19 July 2010
GET THIS BOOKIntroduction to Applied Statistical Signal Analysis

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

An Introduction to Statistical Signal Processing

An Introduction to Statistical Signal Processing
  • Author : Robert M. Gray,Lee D. Davisson
  • Publisher : Cambridge University Press
  • Release : 02 December 2004
GET THIS BOOKAn Introduction to Statistical Signal Processing

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

Introduction to Applied Statistical Signal Analysis

Introduction to Applied Statistical Signal Analysis
  • Author : Richard Shiavi
  • Publisher : Unknown Publisher
  • Release : 18 May 1999
GET THIS BOOKIntroduction to Applied Statistical Signal Analysis

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

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  • Author : Karim G. Oweiss
  • Publisher : Academic Press
  • Release : 22 September 2010
GET THIS BOOKStatistical Signal Processing for Neuroscience and Neurotechnology

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

Statistical Signal Processing of Complex-Valued Data

Statistical Signal Processing of Complex-Valued Data
  • Author : Peter J. Schreier,Louis L. Scharf
  • Publisher : Cambridge University Press
  • Release : 04 February 2010
GET THIS BOOKStatistical Signal Processing of Complex-Valued Data

Complex-valued random signals are embedded in the very fabric of science and engineering, yet the usual assumptions made about their statistical behavior are often a poor representation of the underlying physics. This book deals with improper and noncircular complex signals, which do not conform to classical assumptions, and it demonstrates how correct treatment of these signals can have significant payoffs. The book begins with detailed coverage of the fundamental theory and presents a variety of tools and algorithms for dealing

Introduction to Statistical Signal Processing with Applications

Introduction to Statistical Signal Processing with Applications
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  • Publisher : Unknown Publisher
  • Release : 18 May 1996
GET THIS BOOKIntroduction to Statistical Signal Processing with Applications

An Introduction to Statistical Signal Processing with Applications covers basic techniques in the processing of stochastic signals and illustrate their use in a variety of specific applications. The book presents both detection and estimation in a clear, concise fashion and reflects recent developments and shifting emphases in the field.

Digital and Statistical Signal Processing

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  • Author : Anastasia Veloni,Nikolaos Miridakis,Erysso Boukouvala
  • Publisher : CRC Press
  • Release : 03 October 2018
GET THIS BOOKDigital and Statistical Signal Processing

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

Statistical Signal Processing

Statistical Signal Processing
  • Author : Swagata Nandi,Debasis Kundu
  • Publisher : Springer Nature
  • Release : 21 August 2020
GET THIS BOOKStatistical Signal Processing

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

Probability, Random Processes, and Statistical Analysis

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  • Author : Hisashi Kobayashi,Brian L. Mark,William Turin
  • Publisher : Cambridge University Press
  • Release : 15 December 2011
GET THIS BOOKProbability, Random Processes, and Statistical Analysis

Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and Itô process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum–Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and

Biosignal and Medical Image Processing

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  • Author : John L. Semmlow,Benjamin Griffel
  • Publisher : CRC Press
  • Release : 01 October 2021
GET THIS BOOKBiosignal and Medical Image Processing

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 classify

Statistical Signal Processing

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  • Author : T. Chonavel
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKStatistical Signal Processing

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.

Random Signal Processing

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  • Author : Dwight F. Mix
  • Publisher : Macmillan College
  • Release : 18 May 1995
GET THIS BOOKRandom Signal Processing

Providing detailed coverage of Wiener filtering and Kalman filtering, this book presents a coherent treatment of estimation theory and an in-depth look at detection theory for communication and pattern recognition.

Statistical Methods in Control & Signal Processing

Statistical Methods in Control & Signal Processing
  • Author : Tohru Katayama,Sueo Sugimoto
  • Publisher : CRC Press
  • Release : 08 October 2018
GET THIS BOOKStatistical Methods in Control & Signal Processing

Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this work documents developments in statistical modelling, identification, estimation and signal processing. The book covers such topics as subspace methods, stochastic realization, state space modelling, and identification and parameter estimation.

Introduction to Modeling in Physiology and Medicine

Introduction to Modeling in Physiology and Medicine
  • Author : Claudio Cobelli,Ewart Carson
  • Publisher : Elsevier
  • Release : 06 February 2008
GET THIS BOOKIntroduction to Modeling in Physiology and Medicine

This unified modeling textbook for students of biomedical engineering provides a complete course text on the foundations, theory and practice of modeling and simulation in physiology and medicine. It is dedicated to the needs of biomedical engineering and clinical students, supported by applied BME applications and examples. Developed for biomedical engineering and related courses: speaks to BME students at a level and in a language appropriate to their needs, with an interdisciplinary clinical/engineering approach, quantitative basis, and many applied