Minimax Robustness In Signal Processing For Communications

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Minimax Robustness in Signal Processing for Communications

Author : Muhammad Danish Nisar
Publisher : Shaker
Page : 18 pages
File Size : 49,5 Mb
Release : 2011-08-01
Category : Technology & Engineering
ISBN : 9783844003321

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Minimax Robustness in Signal Processing for Communications by Muhammad Danish Nisar Pdf

Abstract: From a signal processing for communications perspective, three fundamental transceiver design components are the channel precoder, the channel estimator, and the channel equalizer. The optimal design of these blocks is typically formulated as an optimization problem with a certain objective function, and a given constraint set. However, besides the objective function and the constraint set, their optimal design crucially depends upon the adopted system model and the assumed system state. While, optimization under a perfect knowledge of these underlying parameters (system model and state) is relatively straight forward and well explored, the optimization under their imperfect (partial or uncertain) knowledge is more involved and cumbersome. Intuitively, the central question that arises here is: should we fully trust the available imperfect knowledge of the underlying parameters, should we just ignore it, or should we go for an “intermediate” approach? This thesis deals with three crucial transceiver design problems from a signal processing for communications perspective, and attempts to answer the fundamental question of how to handle the presence of uncertainty about the design parameters in the respective optimization problem formulations.

Robust Signal Processing for Wireless Communications

Author : Frank Dietrich
Publisher : Springer Science & Business Media
Page : 280 pages
File Size : 54,7 Mb
Release : 2007-10-25
Category : Technology & Engineering
ISBN : 9783540742494

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Robust Signal Processing for Wireless Communications by Frank Dietrich Pdf

Optimization of adaptive signal processing algorithms for wireless communications is based on a model of the underlying propagation channel. In practice, this model is never known perfectly. For example, its parameters have to be estimated and are only known with significant errors. In this book, a systematic treatment of this practical design problem is provided.

Convex Optimization in Signal Processing and Communications

Author : Daniel P. Palomar,Yonina C. Eldar
Publisher : Cambridge University Press
Page : 513 pages
File Size : 46,8 Mb
Release : 2010
Category : Computers
ISBN : 9780521762229

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Convex Optimization in Signal Processing and Communications by Daniel P. Palomar,Yonina C. Eldar Pdf

Leading experts provide the theoretical underpinnings of the subject plus tutorials on a wide range of applications, from automatic code generation to robust broadband beamforming. Emphasis on cutting-edge research and formulating problems in convex form make this an ideal textbook for advanced graduate courses and a useful self-study guide.

Cognitive Radio Communication and Networking

Author : Robert Caiming Qiu,Zhen Hu,Husheng Li,Michael C. Wicks
Publisher : John Wiley & Sons
Page : 496 pages
File Size : 54,8 Mb
Release : 2012-09-10
Category : Technology & Engineering
ISBN : 9781118376294

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Cognitive Radio Communication and Networking by Robert Caiming Qiu,Zhen Hu,Husheng Li,Michael C. Wicks Pdf

The author presents a unified treatment of this highly interdisciplinary topic to help define the notion of cognitive radio. The book begins with addressing issues such as the fundamental system concept and basic mathematical tools such as spectrum sensing and machine learning, before moving on to more advanced concepts and discussions about the future of cognitive radio. From the fundamentals in spectrum sensing to the applications of cognitive algorithms to radio communications, and discussion of radio platforms and testbeds to show the applicability of the theory to practice, the author aims to provide an introduction to a fast moving topic for students and researchers seeking to develop a thorough understanding of cognitive radio networks. Examines basic mathematical tools before moving on to more advanced concepts and discussions about the future of cognitive radio Describe the fundamentals of cognitive radio, providing a step by step treatment of the topics to enable progressive learning Includes questions, exercises and suggestions for extra reading at the end of each chapter Topics covered in the book include: Spectrum Sensing: Basic Techniques; Cooperative Spectrum Sensing Wideband Spectrum Sensing; Agile Transmission Techniques: Orthogonal Frequency Division Multiplexing Multiple Input Multiple Output for Cognitive Radio; Convex Optimization for Cognitive Radio; Cognitive Core (I): Algorithms for Reasoning and Learning; Cognitive Core (II): Game Theory; Cognitive Radio Network IEEE 802.22: The First Cognitive Radio Wireless Regional Area Network Standard, and Radio Platforms and Testbeds.

Research in Progress

Author : Anonim
Publisher : Unknown
Page : 588 pages
File Size : 42,6 Mb
Release : 1982
Category : Military research
ISBN : NYPL:33433022818789

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Research in Progress by Anonim Pdf

Robust and Distributed Hypothesis Testing

Author : Gökhan Gül
Publisher : Springer
Page : 156 pages
File Size : 51,5 Mb
Release : 2017-03-08
Category : Technology & Engineering
ISBN : 9783319492865

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Robust and Distributed Hypothesis Testing by Gökhan Gül Pdf

This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the book describes the derivation of theoretical bounds in minimax decentralized hypothesis testing, which have not yet been known. As a timely report on the state-of-the-art in robust hypothesis testing, this book is mainly intended for postgraduates and researchers in the field of electrical and electronic engineering, statistics and applied probability. Moreover, it may be of interest for students and researchers working in the field of classification, pattern recognition and cognitive radio.

Stochastic Game Strategies and their Applications

Author : Bor-Sen Chen
Publisher : CRC Press
Page : 600 pages
File Size : 44,8 Mb
Release : 2019-07-31
Category : Mathematics
ISBN : 9780429780516

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Stochastic Game Strategies and their Applications by Bor-Sen Chen Pdf

Game theory involves multi-person decision making and differential dynamic game theory has been widely applied to n-person decision making problems, which are stimulated by a vast number of applications. This book addresses the gap to discuss general stochastic n-person noncooperative and cooperative game theory with wide applications to control systems, signal processing systems, communication systems, managements, financial systems, and biological systems. H∞ game strategy, n-person cooperative and noncooperative game strategy are discussed for linear and nonlinear stochastic systems along with some computational algorithms developed to efficiently solve these game strategies.

Optimal and Robust State Estimation

Author : Yuriy S. Shmaliy,Shunyi Zhao
Publisher : John Wiley & Sons
Page : 484 pages
File Size : 40,7 Mb
Release : 2022-07-20
Category : Technology & Engineering
ISBN : 9781119863090

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Optimal and Robust State Estimation by Yuriy S. Shmaliy,Shunyi Zhao Pdf

A unified and systematic theoretical framework for solving problems related to finite impulse response (FIR) estimate Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches is a comprehensive investigation into batch state estimators and recursive forms. The work begins by introducing the reader to the state estimation approach and provides a brief historical overview. Next, the work discusses the specific properties of finite impulse response (FIR) state estimators. Further chapters give the basics of probability and stochastic processes, discuss the available linear and nonlinear state estimators, deal with optimal FIR filtering, and consider a limited memory batch and recursive algorithms. Other topics covered include solving the q-lag FIR smoothing problem, introducing the receding horizon (RH) FIR state estimation approach, and developing the theory of FIR state estimation under disturbances. The book closes by discussing the theory of FIR state estimation for uncertain systems and providing several applications where the FIR state estimators are used effectively. Key concepts covered in the work include: A holistic overview of the state estimation approach, which arose from the need to know the internal state of a real system, given that the input and output are both known Optimal, optimal unbiased, maximum likelihood, and unbiased and robust finite impulse response (FIR) structures FIR state estimation approach along with the infinite impulse response (IIR) and Kalman approaches Cost functions and the most critical properties of FIR and IIR state estimates Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches was written for professionals in the fields of microwave engineering, system engineering, and robotics who wish to move towards solving finite impulse response (FIR) estimate issues in both theoretical and practical applications. Graduate and senior undergraduate students with coursework dealing with state estimation will also be able to use the book to gain a valuable foundation of knowledge and become more adept in their chosen fields of study.

Issues in Electronic Circuits, Devices, and Materials: 2011 Edition

Author : Anonim
Publisher : ScholarlyEditions
Page : 2454 pages
File Size : 41,6 Mb
Release : 2012-01-09
Category : Technology & Engineering
ISBN : 9781464963735

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Issues in Electronic Circuits, Devices, and Materials: 2011 Edition by Anonim Pdf

Issues in Electronic Circuits, Devices, and Materials: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Electronic Circuits, Devices, and Materials. The editors have built Issues in Electronic Circuits, Devices, and Materials: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Electronic Circuits, Devices, and Materials in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Electronic Circuits, Devices, and Materials: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Minimax Approaches to Robust Model Predictive Control

Author : Johan Löfberg
Publisher : Linköping University Electronic Press
Page : 196 pages
File Size : 52,5 Mb
Release : 2003-04-11
Category : Predictive control
ISBN : 9789173736220

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Minimax Approaches to Robust Model Predictive Control by Johan Löfberg Pdf

Controlling a system with control and state constraints is one of the most important problems in control theory, but also one of the most challenging. Another important but just as demanding topic is robustness against uncertainties in a controlled system. One of the most successful approaches, both in theory and practice, to control constrained systems is model predictive control (MPC). The basic idea in MPC is to repeatedly solve optimization problems on-line to find an optimal input to the controlled system. In recent years, much effort has been spent to incorporate the robustness problem into this framework. The main part of the thesis revolves around minimax formulations of MPC for uncertain constrained linear discrete-time systems. A minimax strategy in MPC means that worst-case performance with respect to uncertainties is optimized. Unfortunately, many minimax MPC formulations yield intractable optimization problems with exponential complexity. Minimax algorithms for a number of uncertainty models are derived in the thesis. These include systems with bounded external additive disturbances, systems with uncertain gain, and systems described with linear fractional transformations. The central theme in the different algorithms is semidefinite relaxations. This means that the minimax problems are written as uncertain semidefinite programs, and then conservatively approximated using robust optimization theory. The result is an optimization problem with polynomial complexity. The use of semidefinite relaxations enables a framework that allows extensions of the basic algorithms, such as joint minimax control and estimation, and approx- imation of closed-loop minimax MPC using a convex programming framework. Additional topics include development of an efficient optimization algorithm to solve the resulting semidefinite programs and connections between deterministic minimax MPC and stochastic risk-sensitive control. The remaining part of the thesis is devoted to stability issues in MPC for continuous-time nonlinear unconstrained systems. While stability of MPC for un-constrained linear systems essentially is solved with the linear quadratic controller, no such simple solution exists in the nonlinear case. It is shown how tools from modern nonlinear control theory can be used to synthesize finite horizon MPC controllers with guaranteed stability, and more importantly, how some of the tech- nical assumptions in the literature can be dispensed with by using a slightly more complex controller.

Optimal Combining and Detection

Author : Jinho Choi
Publisher : Cambridge University Press
Page : 349 pages
File Size : 49,8 Mb
Release : 2010-01-28
Category : Technology & Engineering
ISBN : 9781139486330

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Optimal Combining and Detection by Jinho Choi Pdf

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.

Academic Press Library in Signal Processing

Author : Fulvio Gini,Nikolaos D. Sidiropoulos
Publisher : Academic Press
Page : 1389 pages
File Size : 53,5 Mb
Release : 2013-09-10
Category : Technology & Engineering
ISBN : 9780123972248

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Academic Press Library in Signal Processing by Fulvio Gini,Nikolaos D. Sidiropoulos Pdf

This second 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 communications and radar engineering. 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

Applications in Time-Frequency Signal Processing

Author : Antonia Papandreou-Suppappola
Publisher : CRC Press
Page : 432 pages
File Size : 42,6 Mb
Release : 2018-10-03
Category : Technology & Engineering
ISBN : 9781420042467

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Applications in Time-Frequency Signal Processing by Antonia Papandreou-Suppappola Pdf

Because most real-world signals, including speech, sonar, communication, and biological signals, are non-stationary, traditional signal analysis tools such as Fourier transforms are of limited use because they do not provide easily accessible information about the localization of a given frequency component. A more suitable approach for those studying non-stationary signals is the use of time frequency representations that are functions of both time and frequency. Applications in Time-Frequency Signal Processing investigates the use of various time-frequency representations, such as the Wigner distribution and the spectrogram, in diverse application areas. Other books tend to focus on theoretical development. This book differs by highlighting particular applications of time-frequency representations and demonstrating how to use them. It also provides pseudo-code of the computational algorithms for these representations so that you can apply them to your own specific problems. Written by leaders in the field, this book offers the opportunity to learn from experts. Time-Frequency Representation (TFR) algorithms are simplified, enabling you to understand the complex theories behind TFRs and easily implement them. The numerous examples and figures, review of concepts, and extensive references allow for easy learning and application of the various time-frequency representations.

Robust Correlation

Author : Georgy L. Shevlyakov,Hannu Oja
Publisher : John Wiley & Sons
Page : 353 pages
File Size : 52,7 Mb
Release : 2016-09-19
Category : Mathematics
ISBN : 9781118493458

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Robust Correlation by Georgy L. Shevlyakov,Hannu Oja Pdf

This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.