C++ Neural Networks and Fuzzy Logic: Preface

Table 16.4 Example for Relation R1, with Domains D1 and D2

D1D2

GeorgetteSpanish

GeorgetteItalian

DarrellFrench

DarrellSpanish

DarrellJapanese

ErnieSpanish

ErnieRussian

GraceChinese

GraceFrench

Let’s say a fuzzy database has D1 and D2 as domains. Suppose you have a similarity relation S1 on domain

D1 given by the matrix:

          1     0.4   0.8   0.7

          0.4   1     0.5   0.3

          0.8   0.5   1     0.4

          0.7   0.3   0.4   1

Recall that the entries in this matrix represent the degrees of membership of ordered pairs in the relation S1.

For example, the first row third column element, which is 0.8, in the matrix refers to the degree of

membership of the pair (Georgette, Ernie), since the rows and columns refer to Georgette, Darrell, Ernie and

Grace in that order.

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C++ Neural Networks and Fuzzy Logic:Preface

Example

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