Fundamentals of Stochastic Signals, Systems and Estimation Theory with Worked Examples
Author: Branko Kovačević
Publisher:
Published: 2008
Total Pages: 432
ISBN-13: 9788674663233
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Fundamentals of Stochastic Signals, Systems and Estimation Theory
Author: Branko Kovacevic
Publisher: Springer
Published: 2008-09-08
Total Pages: 380
ISBN-13: 9783540709909
DOWNLOAD EBOOKThe main theme of this book deals with fundamental concepts underlying stochastic signal or linear stochastic systems, their modelling and analysis as well as model-based signal processing. Many examples are included to illustrate the concepts of this book.
Fundamentals of Stochastic Signals, Systems and Estimation Theory
Author: Branko Kovacevic
Publisher: Springer
Published: 2008-06-29
Total Pages: 0
ISBN-13: 9783540709916
DOWNLOAD EBOOKRobust Digital Processing of Speech Signals
Author: Branko Kovacevic
Publisher: Springer
Published: 2017-06-06
Total Pages: 233
ISBN-13: 3319536133
DOWNLOAD EBOOKThis book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in “online” mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors’ research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.
Adaptive Digital Filters
Author: Branko Kovačević
Publisher: Springer Science & Business Media
Published: 2013-06-21
Total Pages: 221
ISBN-13: 3642335616
DOWNLOAD EBOOK“Adaptive Digital Filters” presents an important discipline applied to the domain of speech processing. The book first makes the reader acquainted with the basic terms of filtering and adaptive filtering, before introducing the field of advanced modern algorithms, some of which are contributed by the authors themselves. Working in the field of adaptive signal processing requires the use of complex mathematical tools. The book offers a detailed presentation of the mathematical models that is clear and consistent, an approach that allows everyone with a college level of mathematics knowledge to successfully follow the mathematical derivations and descriptions of algorithms. The algorithms are presented in flow charts, which facilitates their practical implementation. The book presents many experimental results and treats the aspects of practical application of adaptive filtering in real systems, making it a valuable resource for both undergraduate and graduate students, and for all others interested in mastering this important field.
Applications and Optimizations of Kalman Filter and Their Variants
Author: Asadullah Khalid
Publisher: BoD – Books on Demand
Published: 2024-07-17
Total Pages: 204
ISBN-13: 0854665668
DOWNLOAD EBOOKApplications and Optimizations of Kalman Filter and Their Variants is a comprehensive exploration of Kalman filters’ diverse applications and refined optimizations across various domains. It meticulously examines their role in microgrid management, offering adaptive estimation techniques for effective control strategies. The book then delves into distribution system state estimation, showcasing an innovative stochastic programming model using extended Kalman filters for reliable monitoring and control. In the realm of financial modeling, readers gain insights into how Kalman filters enhance trading strategies like pairs trading and partial co-integration, bridging finance and analytics. Moreover, the book discusses Kalman filter optimization, addressing challenges in object tracking and error reduction with techniques like dynamic stochastic approximation algorithms and M-robust estimates. With practical examples and interdisciplinary approaches, this book serves as a valuable resource for researchers, practitioners, and students looking to harness Kalman filter techniques for enhanced efficiency and accuracy across diverse fields.
Fundamentals of Statistical Signal Processing
Author: Steven M. Kay
Publisher: Pearson Education
Published: 2013
Total Pages: 496
ISBN-13: 013280803X
DOWNLOAD EBOOK"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.
An Introduction to Statistical Signal Processing
Author: Robert M. Gray
Publisher: Cambridge University Press
Published: 2004-12-02
Total Pages: 479
ISBN-13: 1139456288
DOWNLOAD EBOOKThis 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.
Fundamentals of Signal Processing in Metric Spaces with Lattice Properties
Author: Andrey Popoff
Publisher: CRC Press
Published: 2017-11-03
Total Pages: 418
ISBN-13: 1351597132
DOWNLOAD EBOOKExploring the interrelation between information theory and signal processing theory, the book contains a new algebraic approach to signal processing theory. Readers will learn this new approach to constructing the unified mathematical fundamentals of both information theory and signal processing theory in addition to new methods of evaluating quality indices of signal processing. The book discusses the methodology of synthesis and analysis of signal processing algorithms providing qualitative increase of signal processing efficiency under parametric and nonparametric prior uncertainty conditions. Examples are included throughout the book to further emphasize new material.
Principles of System Identification
Author: Arun K. Tangirala
Publisher: CRC Press
Published: 2018-10-08
Total Pages: 881
ISBN-13: 143989602X
DOWNLOAD EBOOKMaster Techniques and Successfully Build Models Using a Single Resource Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book focuses on system identification with an emphasis on practice, and concentrates most specifically on discrete-time linear system identification. Useful for Both Theory and Practice The book presents the foundational pillars of identification, namely, the theory of discrete-time LTI systems, the basics of signal processing, the theory of random processes, and estimation theory. It explains the core theoretical concepts of building (linear) dynamic models from experimental data, as well as the experimental and practical aspects of identification. The author offers glimpses of modern developments in this area, and provides numerical and simulation-based examples, case studies, end-of-chapter problems, and other ample references to code for illustration and training. Comprising 26 chapters, and ideal for coursework and self-study, this extensive text: Provides the essential concepts of identification Lays down the foundations of mathematical descriptions of systems, random processes, and estimation in the context of identification Discusses the theory pertaining to non-parametric and parametric models for deterministic-plus-stochastic LTI systems in detail Demonstrates the concepts and methods of identification on different case-studies Presents a gradual development of state-space identification and grey-box modeling Offers an overview of advanced topics of identification namely the linear time-varying (LTV), non-linear, and closed-loop identification Discusses a multivariable approach to identification using the iterative principal component analysis Embeds MATLAB® codes for illustrated examples in the text at the respective points Principles of System Identification: Theory and Practice presents a formal base in LTI deterministic and stochastic systems modeling and estimation theory; it is a one-stop reference for introductory to moderately advanced courses on system identification, as well as introductory courses on stochastic signal processing or time-series analysis.The MATLAB scripts and SIMULINK models used as examples and case studies in the book are also available on the author's website: http://arunkt.wix.com/homepage#!textbook/c397
