Estimation of signal information content for classification
Name
Fisher-2009-Estimation of signal information content for classification.pdf
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206.89 KB
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Adobe PDF
Checksum (MD5)
7988449a6f9f0b42a998545e66f0b520
Author(s)
Fisher, John W., III
Siracusa, Michael
Tieu, Kinh
Date Issued
February 2009
Journal
IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009
Publisher
Institute of Electrical and Electronics Engineers
Citation
Fisher, J.W., M. Siracusa, and Kinh Tieu. “Estimation of Signal Information Content for Classification.” Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th. 2009. 353-358.© 2009 Institute of Electrical and Electronics Engineers.
Version
Final published version
Abstract
Information measures have long been studied in the context of hypothesis testing leading to variety of bounds on performance based on the information content of a signal or the divergence between distributions. Here we consider the problem of estimation of information content for high-dimensional signals for purposes of classification. Direct estimation of information for high-dimensional signals is generally not tractable therefore we consider an extension to a method first suggested in (J.W. Fisher III and J.C. Principle, 1998) in which high dimensional signals are mapped to lower dimensional feature spaces yielding lower bounds on information content. We develop an affine-invariant gradient method and examine the utility of the resulting estimates for predicting classification performance empirically.
Subjects
feature extraction
information measures
invariance
mutual information
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/DSP.2009.4785948
