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    Predictive information in Gaussian processes with application to music analysis 
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    • Predictive information in Gaussian processes with application to music analysis
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    Predictive information in Gaussian processes with application to music analysis

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    Accepted version (316.5Kb)
    Volume
    8085 LNCS
    Pagination
    650 - 657
    Publisher
    Springer Berlin Heidelberg
    Publisher URL
    http://link.springer.com/chapter/10.1007/978-3-642-40020-9_72
    ISBN-13
    9783642400193
    DOI
    10.1007/978364240020972
    Issue
    XVIII
    ISSN
    0302-9743
    Metadata
    Show full item record
    Abstract
    We describe an information-theoretic approach to the analysis of sequential data, which emphasises the predictive aspects of perception, and the dynamic process of forming and modifying expectations about an unfolding stream of data, characterising these using a set of process information measures. After reviewing the theoretical foundations and the definition of the predictive information rate, we describe how this can be computed for Gaussian processes, including how the approach can be adpated to non-stationary processes, using an online Bayesian spectral estimation method to compute the Bayesian surprise. We finish with a sample analysis of a recording of Steve Reich’s Drumming
    Authors
    Abdallah, S; Plumbley, M; Geometric Science of Information
    URI
    http://qmro.qmul.ac.uk/xmlui/handle/123456789/5919
    Collections
    • Centre for Digital Music (C4DM) [210]
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