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Adaptive Noise Cancellation Using Partially Recurrent Fuzzy System

机译:基于部分递归模糊系统的自适应噪声消除

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In this paper, a partially recurrent fuzzy system is developed to function as an adaptive noise canceller. In order to cancel noise distorting the information signal, the temporal information (dynamics) underlying the noise source and the distorting noise, which is generated by the noise source passing through some unknown channels, should be captured accurately. For this purpose, short-term memory is embedded into the input layer of the fuzzy system for handling local time information and internal feedback is introduced into the consequent part for processing global time information by virtue of a partially recurrent mechanism. A novel adaptive algorithm is proposed to tune the parameters of the premise and consequent part online. Simulation studies show that the proposed fuzzy system can cancel noise cancellation successfully for nonlinear dynamic channels.
机译:在本文中,部分递归模糊系统被开发来用作自适应噪声消除器。为了消除使信息信号失真的噪声,应该准确地捕获噪声源和失真噪声所基于的时间信息(动力学),该噪声是由噪声源通过一些未知通道生成的。为此,将短期存储器嵌入模糊系统的输入层中,以处理本地时间信息,并通过部分递归机制将内部反馈引入到后续部分中,以处理全局时间信息。提出了一种新颖的自适应算法来在线优化前提和后续部分的参数。仿真研究表明,所提出的模糊系统能够成功消除非线性动态通道的噪声消除。

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