|
Applied Optimal Estimation
Gelb, Arthur 저 | MIT | 20080204
원 → 45,000원
소개 This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation. Even so, theoretical and mathematical concepts are introduced and developed sufficiently to make the book a self-contained source of instruction for readers without prior knowledge of the basic principles of the field. The work is the product of the technical staff of the The Analytic Sciences Corporation (TASC), an organization whose success has resulted largely from its applications of optimal estimation techniques to a wide variety of real situations involving large-scale systems Arthur Gelb writes in the Foreword that "It is our intent throughout to provide a simple and interesting picture of the central issues underlying modern estimation theory and practice. Heuristic, rather than theoretically elegant, arguments are used extensively, with emphasis on physical insights and key questions of practical importance." Numerous illustrative examples, many based on actual applications, have been interspersed throughout the text to lead the student to a concrete understanding of the theoretical material. The inclusion of problems with "built-in" answers at the end of each of the nine chapters further enhances the self-study potential of the text. After a brief historical prelude, the book introduces the mathematics underlying random process theory and state-space characterization of linear dynamic systems. The theory and practice of optimal estimation is them presented, including filtering, smoothing, and prediction. Both linear and non-linear systems, and continuous- and discrete-time cases, are covered in considerable detail. New results are described concerning the application of covariance analysis to non-linear systems and the connection between observers and optimal estimators. The final chapters treat such practical and often pivotal issues as suboptimal structure, and computer loading considerations. This book is an outgrowth of a course given by TASC at a number of US Government facilities. Virtually all of the members of the TASC technical staff have, at one time and in one way or another, contributed to the material contained in the work
국제표준 도서번호(ISBN) : 9780262570480
|
|
|
Software Engineering for Internet Applications
저 | MIT | 20210101
원 → 32,000원
소개 After completing this self-contained course on server-based Internet applications software, students who start with only the knowledge of how to write and debug a computer program will have learned how to build web-based applications on the scale of Amazon.com. Unlike the desktop applications that most students have already learned to build, server-based applications have multiple simultaneous users. This fact, coupled with the unreliability of networks, gives rise to the problems of concurrency...
국제표준 도서번호(ISBN) : 9780262511919
|
|
|
Great Ideas in Computer Science with Java
저 | MIT | 20210101
원 → 15,000원
소개 This book presents the "great ideas" of computer science, condensing a large amount of complex material into a manageable, accessible form; it does so using the Java programming language. The book is based on the problem-oriented approach that has...
국제표준 도서번호(ISBN) : 9780262024976
|
|
|
AI Ethics
Mark Coeckelbergh 저 | MIT | 20200407
원 → 21,580원
소개
국제표준 도서번호(ISBN) : 9780262538190
|
|
|
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems (Computational and Mathematical Modeling of Neural Systems)
Dayan, Peter/ Abbott, L. F. 저 | MIT | 20050901
원 → 65,000원
소개 Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.
The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site.
국제표준 도서번호(ISBN) : 9780262541855
|
|
|
Conceptual Issues in Evolutionary Biology, 3/E
Sober, E. 저 | MIT | 20060901
원 → 49,000원
소개 These essays by leading scientists and philosophers address conceptual issues that arise in the theory and practice of evolutionary biology. The third edition of this widely used anthology has been substantially revised and updated. Four new sections have been added: on women in the evolutionary process, evolutionary psychology, laws in evolutionary theory, and race as social construction or biological reality. Other sections treat fitness, units of selection, adaptationism, reductionism, essentialism, species, phylogenetic inference, cultural evolution, and evolutionary ethics. Each of the twelve sections contains two or three essays that develop different views of the subject at hand. For example, the section on evolutionary psychology offers one essay by two founders of the field and another that questions its main tenets. One sign that a discipline is growing is that there are open questions, with multiple answers still in competition; the essays in this volume demonstrate that evolutionary biology and the philosophy of evolutionary biology are living, growing disciplines. Contributors: Robin O. Andreasen, Kwame Anthony Appiah, David A. Baum, John H. Beatty, David J. Buller, Leda Cosmides, James Donoghue, Steven J. Farris, Joseph Felsenstein, Susan K. Finsen, Joseph Fracchia, Stephen Jay Gould, Sarah Blaffer Hrdy, David L. Hull, Philip Kitcher, R. C. Lewontin, Elisabeth Lloyd, Ernst Mayr, Michael Ruse, John Maynard Smith, Elliott Sober, John Tooby, C. Kenneth Waters, George C. Williams, David Sloan Wilson, E. O. Wilson
국제표준 도서번호(ISBN) : 9780262693387
|
|
|
The Return of the Real: Art and Theory at the End of the Century (The Avante-Garde at the End of the Century)
Foster, Hal 저 | MIT | 20120101
원 → 20,000원
소개 In The Return of the RealHal Foster discusses the development of art and theory since 1960, and reorders the relation between prewar and postwar avant-gardes. Opposed to the assumption that contemporary art is somehow belated, he argues that the avant-garde returns to us from the future, repositioned by innovative practice in the present. And he poses this retroactive model of art and theory against the reactionary undoing of progressive culture that is pervasive today. After the models of art-as-text in the 1970s and art-as-simulacrum in the 1980s; Foster suggests that we are now witness to a return to the real -- to art and theory grounded in the materiality of actual bodies and social sites: If The Return of the Realbegins with a new narrative of the historical avant-garde; it concludes with an original reading of this contemporary situation -- and what it portends for future practices of art and theory, culture and politics.
국제표준 도서번호(ISBN) : 9780262561075
|
|
|
An Introduction to Genetic Algorithms
Michell, Melanie 저 | MIT | 19980206
원 → 49,000원
소개 Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics -- particularly in machine learning, scientific modeling, and artificial life -- and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithmsis accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
국제표준 도서번호(ISBN) : 9780262631853
|
|
|
An Introduction to Computational Learning Theory
Michael J. Kearns 저 | MIT | 19940815
원 → 49,000원
소개 Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.
국제표준 도서번호(ISBN) : 9780262111935
|
|
|
Introduction to Algorithms
Cormen, Thomas H.^Leiserson, Charles E.^Rivest, Ronald L. 저 | MIT | 20090901
원 → 162,000원
소개 Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithmsuniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many new exercises and problems have been added for this edition. As of the third edition, this textbook is published exclusively by the MIT Press.
국제표준 도서번호(ISBN) : 9780262033848
|
| |
|
|
| 현재접속자 명 |
 |
|
|
|
|
|
