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  • Philosophy and Connectionist Theory

    Collections series Developments in Connectionist Theory Series
    The philosophy of cognitive science has recently become one of the most exciting and fastest growing domains of philosophical inquiry and analysis. Until the early 1980s, nearly all of the models developed treated cognitive processes -- like problem solving, language comprehension, memory, and higher visual processing -- as rule-governed symbol manipulation. However, this situation has changed ... En savoir plus

    $116.79 CAD

  • Backpropagation

    Theory, Architectures, and Applications

    Modifié par Yves Chauvin, David E. Rumelhart ...
    Collections series Developments in Connectionist Theory Series
    Composed of three sections, this book presents the most popular training algorithm for neural networks: backpropagation. The first section presents the theory and principles behind backpropagation as seen from different perspectives such as statistics, machine learning, and dynamical systems. The second presents a number of network architectures that may be designed to match the general concepts ... En savoir plus

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  • Mathematical Perspectives on Neural Networks

    Collections series Developments in Connectionist Theory Series
    Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests on a breadth of mathematical background which even few specialists possess. In a format intermediate between a textbook and a collection of research articles, this book has been assembled to present a sample of these results, and to fill in the necessary ... En savoir plus

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  • Neuroscience and Connectionist Theory

    Modifié par Mark A. Gluck, David E. Rumelhart ...
    Collections series Developments in Connectionist Theory Series
    Written for cognitive scientists, psychologists, computer scientists, engineers, and neuroscientists, this book provides an accessible overview of how computational network models are being used to model neurobiological phenomena. Each chapter presents a representative example of how biological data and network models interact with the authors' research. The biological phenomena cover network- or ... En savoir plus

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    This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods ... En savoir plus

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  • System Identification

    Theory for the User

    par Lennart Ljung ...
    The field's leading text, now completely updated.Modeling dynamical systems — theory, methodology, and applications.Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and ... En savoir plus

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  • Pattern Recognition and Machine Learning

    par Y. Anzai ...
    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the ... En savoir plus

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  • Data Analysis

    Modifié par Gérard Govaert ...
    The first part of this book is devoted to methods seeking relevant dimensions of data. The variables thus obtained provide a synthetic description which often results in a graphical representation of the data. After a general presentation of the discriminating analysis, the second part is devoted to clustering methods which constitute another method, often complementary to the methods described in ... En savoir plus

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  • Optimization in Engineering Sciences

    Exact Methods

    The purpose of this book is to present the main methods of static and dynamic optimization. It has been written within the framework of the European Union project – ERRIC (Empowering Romanian Research on Intelligent Information Technologies), funded by the EU’s FP7 Research Potential program and developed in cooperation between French and Romanian teaching researchers.Through the principles of ... En savoir plus

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  • Adaptive Filters

    par Ali H. Sayed ...
    Collections series IEEE Press
    Adaptive filtering is a topic of immense practical and theoretical value, having applications in areas ranging from digital and wireless communications to biomedical systems. This book enables readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. The book consists of eleven parts ... En savoir plus

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  • An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

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  • Introduction To The Theory Of Neural Computation

    par John A. Hertz ...
    Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest. ... En savoir plus

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