Download or read book Random Signals Estimation and Identification written by Nirode Mohanty and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: The techniques used for the extraction of information from received or ob served signals are applicable in many diverse areas such as radar, sonar, communications, geophysics, remote sensing, acoustics, meteorology, med ical imaging systems, and electronics warfare. The received signal is usually disturbed by thermal, electrical, atmospheric, channel, or intentional inter ferences. The received signal cannot be predicted deterministically, so that statistical methods are needed to describe the signal. In general, therefore, any received signal is analyzed as a random signal or process. The purpose of this book is to provide an elementary introduction to random signal analysis, estimation, filtering, and identification. The emphasis of the book is on the computational aspects as well as presentation of com mon analytical tools for systems involving random signals. The book covers random processes, stationary signals, spectral analysis, estimation, optimiz ation, detection, spectrum estimation, prediction, filtering, and identification. The book is addressed to practicing engineers and scientists. It can be used as a text for courses in the areas of random processes, estimation theory, and system identification by undergraduates and graduate students in engineer ing and science with some background in probability and linear algebra. Part of the book has been used by the author while teaching at State University of New York at Buffalo and California State University at Long Beach. Some of the algorithms presented in this book have been successfully applied to industrial projects.
Download or read book Random Signals written by K. Sam Shanmugan and published by John Wiley & Sons. This book was released on 1988 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random Signals: Detection and Data Analysis develops the theory of random processes and its application to the study of systems and analysis of random data. The text covers three important areas: fundamentals and examples of random process models; application of probabilistic models - signal detection, and filtering; and statistical estimation - measurement and analysis of random data to determine the structure and parameter values of probabilistic models. This volume by Breipohl and Shanmugan offers the only one-volume treatment of the fundamentals of random process models, their applications, and data analysis.
Download or read book Random Signal Processing written by Dwight F. Mix and published by Macmillan College. This book was released on 1995 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Introduction to Random Signals Estimation Theory and Kalman Filtering written by M. Sami Fadali and published by Springer Nature. This book was released on with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Signal Detection and Estimation written by H. Vincent Poor and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to introduce the reader to the basic theory of signal detection and estimation. It is assumed that the reader has a working knowledge of applied probabil ity and random processes such as that taught in a typical first-semester graduate engineering course on these subjects. This material is covered, for example, in the book by Wong (1983) in this series. More advanced concepts in these areas are introduced where needed, primarily in Chapters VI and VII, where continuous-time problems are treated. This book is adapted from a one-semester, second-tier graduate course taught at the University of Illinois. However, this material can also be used for a shorter or first-tier course by restricting coverage to Chapters I through V, which for the most part can be read with a background of only the basics of applied probability, including random vectors and conditional expectations. Sufficient background for the latter option is given for exam pIe in the book by Thomas (1986), also in this series.
Download or read book Blind Identification and Separation of Complex valued Signals written by Eric Moreau and published by John Wiley & Sons. This book was released on 2013-10-07 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources – underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory. Contents 1. Mathematical Preliminaries. 2. Estimation by Joint Diagonalization. 3. Maximum Likelihood ICA. About the Authors Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applications to data analysis, telecommunications and radar. Tülay Adali is Professor of Electrical Engineering and Director of the Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, USA. Her research interests concern statistical and adaptive signal processing, with an emphasis on nonlinear and complex-valued signal processing, and applications in biomedical data analysis and communications. Blind identification consists of estimating a multidimensional system through the use of only its output. Source separation is concerned with the blind estimation of the inverse of the system. The estimation is generally performed by using different statistics of the outputs. The authors consider the blind estimation of a multiple input/multiple output (MIMO) system that mixes a number of underlying signals of interest called sources. They also consider the case of direct estimation of the inverse system for the purpose of source separation. They then describe the estimation theory associated with the identifiability conditions and dedicated algebraic algorithms. The algorithms depend critically on (statistical and/or time frequency) properties of complex sources that will be precisely described.
Download or read book Random Signal Processing written by Shaila Dinkar Apte and published by CRC Press. This book was released on 2017-08-15 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and detection. MATLAB simulations are included for each concept with output of the program with case studies and project ideas. The chapters progressively introduce and explain the concepts of random signals and cover multiple applications for signal processing. The book is designed to cater to a wide audience starting from the undergraduates (electronics, electrical, instrumentation, computer, and telecommunication engineering) to the researchers working in the pertinent fields. Key Features: • Aimed at random signal processing with parametric signal processing-using appropriate segment size. • Covers speech, image, medical images, EEG and ECG signal processing. • Reviews optimal detection and estimation. • Discusses parametric modeling and signal processing in transform domain. • Includes MATLAB codes and relevant exercises, case studies and solved examples including multiple choice questions
Download or read book Stochastic Signal Processing written by Johann Frederic Böhme and published by Springer Vieweg. This book was released on 2012 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book intends to provide graduate students in electrical and information science a solid background in stochastic signal processing. Chapter one introduces random signals through measurement noise. Chapter two develops fundamental concepts in probability theory and statistical methods. Chapter three is devoted to stochastic processes, stochastic system theory, and statistical signal processing. The examples are carefully selected. Some of them are aimed at motivating students interested in advanced topics such as signal detection, estimation, spectral analysis and system identification. Problems with solutions and MATLAB exercises are included to encourage self study by researchers or engineers in related areas. The most important concepts in statistics are presented so that linear systems and nonlinear ones as rectifiers with random input and output signals have proper mathematical description and allow statistical inference. Such systems are fundamental to many engineering areas, for example, electronics, measurements, communications and control.
Download or read book A unified approach to detection estimation and system identification written by Sung Kyou Park and published by . This book was released on 1972 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified approach is presented for the problem of simultaneous detection of random signals in additive white Gaussian noise, estimation of the signals and identification of the systems that generate the signals. The approach is based on the state-variable representation for random processes and makes use of the Markovian nature of the state vectors. Optimal solutions are derived for the cases where both the dynamical system for the signal state and the observation data are continuous, and both the system and the observation data are discrete. Optimal solutions are presented in the form of optimal nonlinear filtering for the sufficient statistic for Bayes decision, the signal state-vector and the parameter vector that characterize the system. This problem is treated for both single shot and multishot observations of various signal sequences. In addition, the optimal state vector estimation for the linear systems where the initial state vector is non-Gaussian is presented. (Author Modified Abstract).
Download or read book Random Signals and Noise written by Shlomo Engelberg and published by CRC Press. This book was released on 2018-10-03 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the nature of random signals and noise is critically important for detecting signals and for reducing and minimizing the effects of noise in applications such as communications and control systems. Outlining a variety of techniques and explaining when and how to use them, Random Signals and Noise: A Mathematical Introduction focuses on applications and practical problem solving rather than probability theory. A Firm Foundation Before launching into the particulars of random signals and noise, the author outlines the elements of probability that are used throughout the book and includes an appendix on the relevant aspects of linear algebra. He offers a careful treatment of Lagrange multipliers and the Fourier transform, as well as the basics of stochastic processes, estimation, matched filtering, the Wiener-Khinchin theorem and its applications, the Schottky and Nyquist formulas, and physical sources of noise. Practical Tools for Modern Problems Along with these traditional topics, the book includes a chapter devoted to spread spectrum techniques. It also demonstrates the use of MATLAB® for solving complicated problems in a short amount of time while still building a sound knowledge of the underlying principles. A self-contained primer for solving real problems, Random Signals and Noise presents a complete set of tools and offers guidance on their effective application.
Download or read book Stochastic Processes Estimation and Control written by Jason L. Speyer and published by SIAM. This book was released on 2008-11-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to stochastic optimal control. The book covers discrete- and continuous-time stochastic dynamic systems leading to the derivation of the Kalman filter, its properties, and its relation to the frequency domain Wiener filter aswell as the dynamic programming derivation of the linear quadratic Gaussian (LQG) and the linear exponential Gaussian (LEG) controllers and their relation to HÝsubscript 2¨ and HÝsubscript Ýinfinity¨¨ controllers and system robustness. This book is suitable for first-year graduate students in electrical, mechanical, chemical, and aerospace engineering specializing in systems and control. Students in computer science, economics, and possibly business will also find it useful.
Download or read book Random Signals for Engineers Using MATLAB and Mathcad Text written by Richard C. Jaffe and published by Springer Science & Business Media. This book was released on 2000-09-08 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Windows-Version
Download or read book Random Signals and Systems written by Bernard Picinbono and published by . This book was released on 1993 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: A presentation of random signals and systems focusing on applications often encountered in practice. It makes use of geometrical methods, contains a systematic presentation of covariance matrices, and includes a discussion of Gaussian complex random vectors.
Download or read book Signal Analysis and Prediction written by Ales Prochazka and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book System Identification Parameter and State Estimation written by P. Eykhoff and published by Chichester ; New York : Wiley. This book was released on 1974-05-23 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Identification of Physical Systems written by Rajamani Doraiswami and published by John Wiley & Sons. This book was released on 2014-07-29 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identification of a physical system deals with the problem of identifying its mathematical model using the measured input and output data. As the physical system is generally complex, nonlinear, and its input–output data is corrupted noise, there are fundamental theoretical and practical issues that need to be considered. Identification of Physical Systems addresses this need, presenting a systematic, unified approach to the problem of physical system identification and its practical applications. Starting with a least-squares method, the authors develop various schemes to address the issues of accuracy, variation in the operating regimes, closed loop, and interconnected subsystems. Also presented is a non-parametric signal or data-based scheme to identify a means to provide a quick macroscopic picture of the system to complement the precise microscopic picture given by the parametric model-based scheme. Finally, a sequential integration of totally different schemes, such as non-parametric, Kalman filter, and parametric model, is developed to meet the speed and accuracy requirement of mission-critical systems. Key features: Provides a clear understanding of theoretical and practical issues in identification and its applications, enabling the reader to grasp a clear understanding of the theory and apply it to practical problems Offers a self-contained guide by including the background necessary to understand this interdisciplinary subject Includes case studies for the application of identification on physical laboratory scale systems, as well as number of illustrative examples throughout the book Identification of Physical Systems is a comprehensive reference for researchers and practitioners working in this field and is also a useful source of information for graduate students in electrical, computer, biomedical, chemical, and mechanical engineering.
Download or read book Introduction to Random Signals and Noise written by Wim C. Van Etten and published by John Wiley & Sons. This book was released on 2006-02-03 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding, this text provides a clear introduction to the fundamentals of stochastic processes and their practical applications to random signals and noise. With worked examples, problems, and detailed appendices, Introduction to Random Signals and Noise gives the reader the knowledge to design optimum systems for effectively coping with unwanted signals. Key features: Considers a wide range of signals and noise, including analogue, discrete-time and bandpass signals in both time and frequency domains. Analyses the basics of digital signal detection using matched filtering, signal space representation and correlation receiver. Examines optimal filtering methods and their consequences. Presents a detailed discussion of the topic of Poisson processes and shot noise. An excellent resource for professional engineers developing communication systems, semiconductor devices, and audio and video equipment, this book is also ideal for senior undergraduate and graduate students in Electronic and Electrical Engineering.
