Autonomous Learning Systems: from Data Streams to Knowledge in Real-Time

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    Autonomous Learning Systems is the result of over a decade of focused research and studies in this emerging area which spans a number of well-known and well-established disciplines that include machine learning, system identification, data mining, fuzzy logic, neural networks, neuro-fuzzy systems, control theory and pattern recognition. The evolution of these systems has been both industry-driven with an increasing demand from sectors such as defence and security, aerospace and advanced process industries, bio-medicine and intelligent transportation, as well as research-driven there is a strong trend of innovation of all of the above well-established research disciplines that is linked to their on-line and real-time application; their adaptability and flexibility. Providing an introduction to the key technologies, detailed technical explanations of the methodology, and an illustration of the practical relevance of the approach with a wide range of applications, this book addresses the challenges of autonomous learning systems with a systematic approach that lays the foundations for a fast growing area of research that will underpin a range of technological applications vital to both industry and society. Key features: * Presents the subject systematically from explaining the fundamentals to illustrating the proposed approach with numerous applications. * Covers a wide range of applications in fields including unmanned vehicles/robotics, oil refineries, chemical industry, evolving user behaviour and activity recognition. * Reviews traditional fields including clustering, classification, control, fault detection and anomaly detection, filtering and estimation through the prism of evolving and autonomously learning mechanisms. * Accompanied by a website hosting additional material, including the software toolbox and lecture notes. Autonomous Learning Systems provides a one-stop shop on the subject for academics, students, researchers and practicing engineers. It is also a valuable reference for Government agencies and software developers.

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    Number of Pages: 298
    Format(s): Hardback - ISBN: 9781119951520
    Publication Date:
    Listed in: Electronics & communications engineering, Machine learning
    Publisher: John Wiley & Sons Inc

    Books by Plamen Angelov

    Hardback

    RRP: £87.50

    Sale Price: £54.96

    Save: £32.54 per copy!

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