Perceptual Reasoning for Perceptual Computing: A Similarity-Based Approach
IEEE Transactions on Fuzzy SystemsPublished 24 September 2009
Dongrui Wu, Jerry M. Mendel
Citations66
SJR quartileQ1
SJR score3.61
SNIP2.80
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TL;DR
A comparative study shows that S-PR leads to output FOUs that resemble word FOU’s, which are obtained from subject data, much more closely than FI-PR; hence, S- PR is a better choice for a CWW engine thanFI-PR.
Abstract
Perceptual reasoning (PR) is an approximate reasoning method that can be used as a computing-with-words (CWW) engine in perceptual computing. There can be different approaches to implement PR, e.g., firing-interval-based PR (FI-PR), which has been proposed in J. M. Mendel and D. Wu, IEEE Trans. Fuzzy Syst. , vol. 16, no. 6, pp. 1550-1564, Dec. 2008 and similarity-based PR (S-PR), which is proposed in this paper. Both approaches satisfy the requirement on a CWW engine that the result of combining fired rules should lead to a footprint of uncertainty (FOU) that resembles the three kinds of FOUs in a CWW codebook. A comparative study shows that S-PR leads to output FOUs that resemble word FOUs, which are obtained from subject data, much more closely than FI-PR; hence, S-PR is a better choice for a CWW engine than FI-PR.
Keywords
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