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The multiple signal demixing and parameter estimation problems that result from the impacts of background noise and interference are issues that are frequently encountered in the fields of radar, sonar, communications, and navigation. Research in the signal processing and control fields has always focused on improving the estimation performance of parameter estimation methods at low SNR and maintaining the robustness of estimations in the presence of model errors. This book presents a universal and robust relaxation estimation method (RELAX), and introduces its basic principles and applications in the fields of classical line spectrum estimation, time of delay estimation, DOA estimation, and radar target imaging. This information is explained comprehensively and in great detail, and uses metaphors pertaining to romantic relationships to visualize the basic problems of parameter estimation, the basic principles of the five types of classical parameter estimation methods, and the relationships between these principles. The book serves as a reference for scientists and technologists in the fields of signal processing and control, while also providing relevant information for graduate students in the related fields.
The multiple signal demixing and parameter estimation problems that result from the impacts of background noise and interference are issues that are frequently encountered in the fields of radar, sonar, communications, and navigation. Research in the signal processing and control fields has always focused on improving the estimation performance of parameter estimation methods at low SNR and maintaining the robustness of estimations in the presence of model errors. This book presents a universal and robust relaxation estimation method (RELAX), and introduces its basic principles and applications in the fields of classical line spectrum estimation, time of delay estimation, DOA estimation, and radar target imaging. This information is explained comprehensively and in great detail, and uses metaphors pertaining to romantic relationships to visualize the basic problems of parameter estimation, the basic principles of the five types of classical parameter estimation methods, and the relationships between these principles. The book serves as a reference for scientists and technologists in the fields of signal processing and control, while also providing relevant information for graduate students in the related fields.
Presented in a tutorial style, this comprehensive treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Numerous examples clarify procedures and methods. 1995 edition.
Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
More than a decade ago, world-renowned control systems authority Frank L. Lewis introduced what would become a standard textbook on estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic text, and Lewis enlisted the aid of two accomplished experts to bring the book completely up to date with the estimation methods driving today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition reflects new developments in estimation theory and design techniques. As the title suggests, the major feature of this edition is the inclusion of robust methods. Three new chapters cover the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems. Modern Tools for Tomorrow's Engineers This text overflows with examples that highlight practical applications of the theory and concepts. Design algorithms appear conveniently in tables, allowing students quick reference, easy implementation into software, and intuitive comparisons for selecting the best algorithm for a given application. In addition, downloadable MATLAB® code allows students to gain hands-on experience with industry-standard software tools for a wide variety of applications. This cutting-edge and highly interactive text makes teaching, and learning, estimation methods easier and more modern than ever.
This textbook offers a concise yet rigorous introduction to calculus of variations and optimal control theory, and is a self-contained resource for graduate students in engineering, applied mathematics, and related subjects. Designed specifically for a one-semester course, the book begins with calculus of variations, preparing the ground for optimal control. It then gives a complete proof of the maximum principle and covers key topics such as the Hamilton-Jacobi-Bellman theory of dynamic programming and linear-quadratic optimal control. Calculus of Variations and Optimal Control Theory also traces the historical development of the subject and features numerous exercises, notes and references at the end of each chapter, and suggestions for further study. Offers a concise yet rigorous introduction Requires limited background in control theory or advanced mathematics Provides a complete proof of the maximum principle Uses consistent notation in the exposition of classical and modern topics Traces the historical development of the subject Solutions manual (available only to teachers) Leading universities that have adopted this book include: University of Illinois at Urbana-Champaign ECE 553: Optimum Control Systems Georgia Institute of Technology ECE 6553: Optimal Control and Optimization University of Pennsylvania ESE 680: Optimal Control Theory University of Notre Dame EE 60565: Optimal Control
Universal Economics is a new work that bears a strong resemblance to its two predecessors, University Economics (1964, 1967, 1972) and Exchange and Production (1969, 1977, 1983). Collaborating again, Professors Alchian and Allen have written a fresh presentation of the analytical tools employed in the economic way of thinking. More than any other principles textbook, Universal Economics develops the critical importance of property rights to the existence and success of market economies. The authors explain the interconnection between goods prices and productive-asset prices and how market-determined interest rates bring about the allocation of resources toward the satisfaction of consumption demands versus saving/investment priorities. They show how the crucial role of prices in a market economy cannot be well understood without a firm grasp of the role of money in a modern world. The Alchian and Allen application of information and search-cost analysis to the subject of money, price determination, and inflation is unique in the teaching of economic principles. No one has ever done price theory better than Alchian -- that is, no one has ever excelled Alchians ability to explain the reason, role, and nuances of prices, of competition, and of property rights. And only a precious few -- I can count them on my fingers -- have a claim for being considered to have done price theory as well as he did it. -- Donald Boudreaux, George Mason University. Armen A. Alchian (19142013), one of the twentieth centurys great teachers of economic science, taught at UCLA from 1958 to 1984. Founder of the UCLA tradition in economics, he has become recognized as one of the most influential voices in the areas of market structure, property rights, and the theory of the firm. William R. Allen taught at Washington University prior to joining the UCLA faculty in 1952. Along with research primarily in international economics and the history of economic theory, he has concentrated on teaching economics. Universal Economics is his third textbook collaboration with Armen Alchian. Jerry L. Jordan wrote his doctoral dissertation under the direction of Armen Alchian. He was Dean of the School of Management at the University of New Mexico, a member of President Reagans Council of Economic Advisors and of the U.S. Gold Commission, Director of Research of the Federal Reserve Bank of Saint Louis, and President and CEO of the Federal Reserve Bank of Cleveland.
A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.