Under fuzzy environment, the fuzzy extension matrix approach can generate a set of fuzzy rules from examples according to the minimum fuzzy entropy criterion of the path.
在模糊环境下，模糊扩张矩阵算法根据路径的最小模糊信息熵标准，从示例中归纳产生一组模糊规则。
Due to introduce of the fuzzy idea, the fuzzy extension matrix can deal with uncertainty associated with human thinking and perception, so it is used more and more widely.
而模糊扩张矩阵是在扩张矩阵基础上引入了模糊思想，使之能处理与人的思维和感觉有关的不确定性数据，因而得到了广泛的应用。
Compared with the crisp extension matrix, the proposed method has the capability of handling fuzzy representation and tolerating noisy data or missing data.
与清晰情况下相比较，我们所实现的这种算法能够处理模糊数据，对噪音数据和不完整数据有很好的鲁棒性。
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