Abstract
We present an extension to the methods and algorithms for approximation of similarity known as Networks of Comparators. By interpreting the output of the network in terms of discrete fuzzy set we make it possible to employ various defuzzyfication techniques for the purpose of establishing a unique value of the output of comparator network. We illustrate the advantages of this approach using two examples.
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APA
Sosnowski, Ł., & Szczuka, M. (2018). Defuzzyfication in interpretation of comparator networks. In Communications in Computer and Information Science (Vol. 854, pp. 467–479). Springer Verlag. https://doi.org/10.1007/978-3-319-91476-3_39
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