模糊逻辑有限状态机模型的综合与分析

J. Grantner, M. Patyra
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引用次数: 35

摘要

大多数语言模型的一个共同缺点是它们本质上是静态的,时间不是描述过程模型行为的参数,或者它们不能响应系统输入的特定变化序列。动态语言模型可以通过模糊自动机实现。在可行的解决方案中,目前模糊逻辑RISC处理器和模糊逻辑有限状态机(ASIC)似乎是最有前途的。后一种方法被考虑在内。本文详细讨论了模糊状态-模糊输出有限状态机(FSM)的模型。引入状态隶属函数(SMF),提出了利用SMF实现脆状态模糊输出(CSFO) FSM的FSFO FSM。提出了基于CSFO和FSFO FSM的多变量模型和推理方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis and analysis of fuzzy logic finite state machine models
A common drawback of most linguistic models is that they are essentially static, time is not a parameter in describing the behavior of the process model, or they are unable to respond to a specific sequence of changes at the inputs of the system. Dynamic linguistic models can be implemented by fuzzy automata. Of the feasible solutions, at present, fuzzy logic RISC processors and fuzzy logic finite state machines (ASIC) seem to be most promising. The latter approach is taken into consideration. In this paper the model of the fuzzy-state-fuzzy-output (FSFO) finite state machine (FSM) is discussed in detail. The state membership function (SMF) is introduced and the FSFO FSM implementation by means of crisp-state-fuzzy-output (CSFO) FSM using SMF is proposed. The multivariable model and inference scheme are suggested based on CSFO and FSFO FSM.<>
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