By Jost J., Xin Y. L.

We receive a Bernstein theorem for distinctive Lagrangian graphs in for arbitrary in basic terms assuming bounded slope yet no quantitative restrict.

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The principal idea behind these theories is that, in addition to being able to assess qualitative and comp arative concepts, a human being is able to a;sess such quantities as distance, size and weight, according to hislher direct perceptions, and hence no numerical measurements or computations are required. In practice, we notice this phenomenon when we are parking our car, playing golf, assessing wine etc. According to the TFIG, which will be the focus in this section, we operate with granules, which are clusters of objects.

First, we calculate the minimum degrees of membership of A and the fuzzy relation (Fig. 4. 2. Premiss A and Fuzzy Relation . 3. Minimum of Premiss A and Fuzzy Relation. , the Max operation, Fig. 4). , a fuzzy set, is our conclusion. 4. Conclusion Yielded by the Max Operation. 1). , the cores may be empty sets). 2. Fuzzy Graphs We can apply the ideas of graph theory to fuzzy relations, particularly when we operate with discrete reference sets. 7. 1 depiCts these intensities.. 1. Intensities of Discrete Fuzzy Relation (From Rows to Columns).

The SC approach may replace Wittgenstein's and Putnam's ideas with granules, which may be imprecise in nature as well as also have partial memberships to the complex tenns to be defined. A possible problem for the TFIG, and particularly for CW, stems from the facts of evolution theory: human being is well experienced in processing images, whereas the processing of words is much more laborious and complicated. Hence, in the long term, the application of linguistic operations seem not to be the final solution to our problems.

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A Bernstein theorem for special Lagrangian graphs by Jost J., Xin Y. L.


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