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Uncertain systems are universal approximators

机译:不确定的系统是普遍的近似器

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Uncertain inference is a process of deriving consequences from uncertain knowledge or evidences via the tool of conditional uncertain set. Based on uncertain inference, uncertain system is a function from its inputs to outputs. This paper proves that uncertain systems are universal approximators, which means that uncertain systems are capable of approximating any continuous function on a compact set to arbitrary accuracy. This result can be viewed as an existence theorem of an optimal uncertain system for a wide variety of problems.
机译:不确定的推断是通过条件不确定集合的工具从不确定知识或证据中导出后果的过程。基于不确定的推断,不确定的系统是从其输入到输出的功能。本文证明了不确定的系统是普遍的近似器,这意味着不确定的系统能够近似于紧凑型到任意精度的任何连续功能。该结果可以被视为最佳不确定系统的存在定理,用于各种问题。

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