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Nonlinear adaptive noise cancellation for two-dimensional signals with adaptive neuro-fuzzy inference systems.

机译：带有自适应神经模糊推理系统的二维信号的非线性自适应噪声消除。

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摘要

Neuro-fuzzy systems are capable of inducing rules from observations, where the adaptive neuro-fuzzy inference system (ANFIS) is an effective method that can be applied to a variety of domains such as pattern recognition, robotics, nonlinear regression, nonlinear system identification, and adaptive signal processing. However, the signals processed by a typical ANFIS are in one dimension, e.g., acoustic signals. In this thesis, we extend the ANFIS method to two-dimensional (2-D) signals. First, the 2-D signal restoration contaminated with Gaussian noise is investigated in nonlinear passage dynamics of orders 2 and 3. We inspect eight types of membership functions (MFs): bell MF, triangle MF, Gaussian MF, two sided MF, pi-shaped MF, product of two sigmoidal MFs, difference of two sigmoidal MFs, and trapezoidal MF. In addition, several other parameters, such as the training epochs, the number of membership functions for each input, the optimization method, the type of output membership functions, and the over-fitting problem, are investigated. Secondly, ANFIS is used to restore the 2-D signals corrupted by salt and pepper noise. Eight types of membership functions and several other parameters are presented. We also compare the effect of the 2-D signal restored by ANFIS with the conventional filters including spatial filters, frequency domain filters, adaptive optimal filter, Wiener filter, and wavelet and wavelet packet.
机译：神经模糊系统能够根据观察结果得出规则，其中自适应神经模糊推理系统（ANFIS）是一种有效的方法，可以应用于各种领域，例如模式识别，机器人技术，非线性回归，非线性系统识别，和自适应信号处理。然而，由典型的ANFIS处理的信号是一维的，例如，声学信号。在本文中，我们将ANFIS方法扩展到二维（2-D）信号。首先，在2和3阶的非线性通道动力学中研究了被高斯噪声污染的二维信号恢复。我们检查了八种隶属函数（MF）：钟形MF，三角形MF，高斯MF，双面MF，pi-形状的MF，两个S型MF的乘积，两个S型MF的差，和梯形MF。此外，还研究了其他几个参数，例如训练时期，每个输入的隶属函数数量，优化方法，输出隶属函数的类型以及过度拟合问题。其次，ANFIS用于恢复被盐和胡椒噪声破坏的二维信号。介绍了八种类型的隶属函数和其他几个参数。我们还将ANFIS恢复的二维信号的效果与常规滤波器进行比较，包括空间滤波器，频域滤波器，自适应最优滤波器，维纳滤波器以及小波和小波包。

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  • 作者

    Qin, Hao.;

  • 作者单位

    University of Guelph (Canada).;

  • 授予单位 University of Guelph (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.Sc.
  • 年度 2005
  • 页码 137 p.
  • 总页数 137
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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