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A study on neural network recognizer based on fuzzy rules and fuzzy inference fuzzy driven neural network recognizer in pattern recognition

机译:基于模糊规则和模糊推理模糊驱动的神经网络识别器的神经网络识别器研究

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In this study, we introduce neural network recognizer based on fuzzy rules and fuzzy inference. The use of neural networks is proposed for efficient implementation of the fuzzy inference and the neural network is a trainable device consisting of some fuzzy rules and three processes, namely, premise, consequence and fuzzy inference processes. The premise process is driven by fuzzy c-means and the consequence processes deals with a polynomial function. A learning algorithm for the neural network recognizer is developed and its performance is compared with that of previous studies.
机译:在这项研究中,我们基于模糊规则和模糊推断引入神经网络识别器。 提出了用于有效实现模糊推理的神经网络,神经网络是由一些模糊规则和三个过程组成的可训练器件,即前提,后果和模糊推断过程。 前提过程是由模糊C型方式驱动的,后果过程涉及多项式功能。 开发了一种用于神经网络识别器的学习算法,其性能与先前研究的性能进行了比较。

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