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Enhancement and FPGA implementation of ANFIS algorithm in digital image processing

机译:ANFIS算法在数字图像处理中的增强和FPGA实现

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Adaptive Neuro Fuzzy Inference System (ANFIS) is a kind of neuro-fuzzy model, combining fuzzy system and neural network. It incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules. Based on Takagi-Sugeno Fuzzy Inference System, ANFIS focus on the accuracy and it is widely used in control and identification systems. However, when the fuzzy rule base is large, it proved to be slow because of the computation time. This paper introduces an enhanced algorithm, implemented on FPGA platform, to speed up the standard ANFIS algorithm in digital image processing.
机译:自适应神经模糊推理系统(ANFIS)是一种将模糊系统与神经网络相结合的神经模糊模型。它通过使用模糊集和由一组IF-THEN模糊规则组成的语言模型,结合了模糊系统的类人推理风格。 ANFIS基于Takagi-Sugeno模糊推理系统,着重于精度,已广泛应用于控制和识别系统中。但是,当模糊规则库较大时,由于计算时间长,因此证明速度较慢。本文介绍了一种在FPGA平台上实现的增强算法,以加快数字图像处理中标准ANFIS算法的速度。

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