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Mamdani fuzzy system: universal approximator to a class of random processes

机译:Mamdani模糊系统:一类随机过程的通用逼近器

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摘要

The issue of fuzzy systems as universal approximators has drawn significant attention, but all results obtained are restricted to deterministic input-output (I/O) relationships. It should be noted that, in practice, many I/O systems, including fuzzy systems, operate in the environment which is essentially stochastic. In this paper, the Mamdani fuzzy systems are generalized as stochastic systems. By proving the Mamdani systems as universal approximators with L/sup 2/-norm, the approximation capability of the stochastic Mamdani systems to a class of random processes is systematically analyzed. In the mean square sense, such stochastic fuzzy systems are capable of approximating the prescribed random processes with arbitrary accuracy. Further, an efficient learning algorithm for the stochastic Mamdani systems is developed. Finally, a simulation example is employed to demonstrate our results.
机译:作为通用逼近器的模糊系统问题引起了极大的关注,但是获得的所有结果仅限于确定性输入-输出(I / O)关系。应该注意的是,实际上,许多I / O系统(包括模糊系统)在本质上是随机的环境中运行。本文将Mamdani模糊系统概括为随机系统。通过证明Mamdani系统为具有L / sup 2 /范数的通用逼近器,系统地分析了随机Mamdani系统对一类随机过程的逼近能力。在均方意义上,这种随机模糊系统能够以任意精度近似规定的随机过程。此外,开发了一种用于随机Mamdani系统的有效学习算法。最后,通过一个仿真例子来证明我们的结果。

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