Title

The Random Subspace Coarse Coding Scheme for Real-valued Vectors

Abstract

Two coarse coding schemes are considered: the random subspace scheme of the authors, and the modified Kanerva model of Prager et al. (1993). Some properties and characteristics of these schemes are investigated experimentally and by analysing their geometrical interpretation. Both schemes do not require exponential growth of the binary code dimensionality against that of the input space. The random subspace scheme allows the code density to be independent from the maximal dimensionality of hyper-rectangle receptive fields. It is especially important when low-dimensional receptive fields are required, as with classifiers or approximators of real-world data.

Meeting Name

International Joint Conference on Neural Networks (IJCNN'99) (1999: Jul. 10-16, Washington, DC)

Department(s)

Electrical and Computer Engineering

International Standard Serial Number (ISSN)

1098-7576

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1999 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.


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