Download or read book Introduction To Statistical Signal Processing With Applications 1 e written by Mandyam Dhati Srinath and published by . This book was released on 1979 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Statistical Signal Processing written by Robert M. Gray and published by Cambridge University Press. This book was released on 2004-12-02 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Introduction to Statistical Signal Processing with Applications written by Mandyam Dhati Srinath and published by . This book was released on 1996 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book An Introduction to Statistical Signal Processing with Applications written by Mandyam Dhati Srinath and published by John Wiley & Sons. This book was released on 1979 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: In An Introduction to Statistical Signal Processing with Applications, these three author/educators cover basic techniques in the processing of stochastic signals and illustrate their use in a variety of specific applications.
Download or read book Introduction to Applied Statistical Signal Analysis written by Richard Shiavi and published by Elsevier. This book was released on 2010-07-19 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Fundamentals of Statistical Signal Processing written by Steven M. Kay and published by Pearson Education. This book was released on 2013 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: "For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.
Download or read book Introduction to Statistical Signal Processing with Applications written by Mandyam D. Srinath and published by . This book was released on 1999 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Signal Processing for Neuroscience and Neurotechnology written by Karim G. Oweiss and published by Academic Press. This book was released on 2010-09-22 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Academic Press Library in Signal Processing written by Mats Viberg and published by Academic Press. This book was released on 2013-08-31 with total page 1013 pages. Available in PDF, EPUB and Kindle. Book excerpt: This third volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in array and statistical signal processing. With this reference source you will: - Quickly grasp a new area of research - Understand the underlying principles of a topic and its application - Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved - Quick tutorial reviews of important and emerging topics of research in array and statistical signal processing - Presents core principles and shows their application - Reference content on core principles, technologies, algorithms and applications - Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge - Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
Download or read book Digital and Statistical Signal Processing written by Anastasia Veloni and published by CRC Press. This book was released on 2018-10-03 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Signal Processing of Complex Valued Data written by Peter J. Schreier and published by Cambridge University Press. This book was released on 2010-02-04 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 with improper and noncircular signals. It provides a comprehensive account of the main applications, covering detection, estimation, and signal analysis of stationary, nonstationary, and cyclostationary processes. Providing a systematic development from the origin of complex signals to their probabilistic description makes the theory accessible to newcomers. This book is ideal for graduate students and researchers working with complex data in a range of research areas from communications to oceanography.
Download or read book Statistical Signal Processing written by Swagata Nandi and published by Springer Nature. This book was released on 2020-08-21 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Optimal Combining and Detection written by Jinho Choi and published by Cambridge University Press. This book was released on 2010-01-28 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: With signal combining and detection methods now representing a key application of signal processing in communication systems, this book provides a range of key techniques for receiver design when multiple received signals are available. Various optimal and suboptimal signal combining and detection techniques are explained in the context of multiple-input multiple-output (MIMO) systems, including successive interference cancellation (SIC) based detection and lattice reduction (LR) aided detection. The techniques are then analyzed using performance analysis tools. The fundamentals of statistical signal processing are also covered, with two chapters dedicated to important background material. With a carefully balanced blend of theoretical elements and applications, this book is ideal for both graduate students and practising engineers in wireless communications.
Download or read book Algorithms for Statistical Signal Processing written by John G. Proakis and published by . This book was released on 2002 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keeping pace with the expanding, ever more complex applications of DSP, this authoritative presentation of computational algorithms for statistical signal processing focuses on "advanced topics" ignored by other books on the subject. Algorithms for Convolution and DFT. Linear Prediction and Optimum Linear Filters. Least-Squares Methods for System Modeling and Filter Design. Adaptive Filters. Recursive Least-Squares Algorithms for Array Signal Processing. QRD-Based Fast Adaptive Filter Algorithms. Power Spectrum Estimation. Signal Analysis with Higher-Order Spectra. For Electrical Engineers, Computer Engineers, Computer Scientists, and Applied Mathematicians.
Download or read book An Introduction to Digital Signal Processing written by John H. Karl and published by Elsevier. This book was released on 2012-12-02 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Digital Signal Processing is written for those who need to understand and use digital signal processing and yet do not wish to wade through a multi-semester course sequence. Using only calculus-level mathematics, this book progresses rapidly through the fundamentals to advanced topics such as iterative least squares design of IIR filters, inverse filters, power spectral estimation, and multidimensional applications--all in one concise volume. This book emphasizes both the fundamental principles and their modern computer implementation. It presents and demonstrates how simple the actual computer code is for advanced modern algorithms used in DSP. Results of these programs, which the reader can readily duplicate and use on a PC, are presented in many actual computer drawn plots. - Assumes no previous knowledge of signal processing but leads up to very advanced techniquescombines exposition of fundamental principles with practical applications - Includes problems with each chapter - Presents in detail the appropriate computer algorithums for solving problems
Download or read book Introduction to Statistical Signal Processing written by Shiavi and published by Irwin Professional Publishing. This book was released on 1992 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Generalizations of Cyclostationary Signal Processing written by Antonio Napolitano and published by John Wiley & Sons. This book was released on 2012-12-07 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: The relative motion between the transmitter and the receiver modifies the nonstationarity properties of the transmitted signal. In particular, the almost-cyclostationarity property exhibited by almost all modulated signals adopted in communications, radar, sonar, and telemetry can be transformed into more general kinds of nonstationarity. A proper statistical characterization of the received signal allows for the design of signal processing algorithms for detection, estimation, and classification that significantly outperform algorithms based on classical descriptions of signals.Generalizations of Cyclostationary Signal Processing addresses these issues and includes the following key features: Presents the underlying theoretical framework, accompanied by details of their practical application, for the mathematical models of generalized almost-cyclostationary processes and spectrally correlated processes; two classes of signals finding growing importance in areas such as mobile communications, radar and sonar. Explains second- and higher-order characterization of nonstationary stochastic processes in time and frequency domains. Discusses continuous- and discrete-time estimators of statistical functions of generalized almost-cyclostationary processes and spectrally correlated processes. Provides analysis of mean-square consistency and asymptotic Normality of statistical function estimators. Offers extensive analysis of Doppler channels owing to the relative motion between transmitter and receiver and/or surrounding scatterers. Performs signal analysis using both the classical stochastic-process approach and the functional approach, where statistical functions are built starting from a single function of time.
