OWA — Based Computing: Learning Algorithms

Witold Pedrycz ()
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Witold Pedrycz: University of Manitoba, Department of Electrical and Computer Engineering

A chapter in The Ordered Weighted Averaging Operators, 1997, pp 309-320 from Springer

Abstract: Abstract The paradigm of knowledge-based neurocomputing imposes an imperative requirement on the functional elements used in such computational architectures. What has been lacking in standard neurocomputing is an ability of the networks exploited therein to encapsulate all pieces of domain knowledge that are usually available in advance. Any successful symbiosis calls for the satisfaction of several fundamental functional postulates [2]: emerging topologies should easily encapsulate any prior and sometimes qualitative or imprecise domain knowledge an interpretation of the emerging network needs to be straightforward.

Keywords: Performance Index; Unsupervised Learning; Fuzzy Measure; Ordered Weight Average; Entropy Criterion (search for similar items in EconPapers)
Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4615-6123-1_23

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DOI: 10.1007/978-1-4615-6123-1_23

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