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Design of Fuzzy Neural Network for Function Approximation and Classification

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Academic year: 2017

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Figure 3: Fuzzification of numeric input.
Figure 4: Example of overlapping: c 1 > c 2 and σ 1 < σ 2 . i th input node (numeric or linguistic) j th rule nodeεijFuzzy signalS(xi)=(ci, σi)Fuzzy weightwij=(cij, σij)Mutual subsethoodXi
Table 1: Details of different learning schedules used for simulation studies
Table 2: Root mean square errors for different rule count and learning schedules (LS) for 250 epochs
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