摘要
本文提出了一种基于模糊神经网络的噪声自适应消除方法,介绍了该方法的原理及实现算法,并利用特殊函数和一定的噪声作为样本信号,建立了基于模糊神经网络的自适应噪声消除模型。通过该模型对有用信号的参数进行了辨识,仿真结果表明该方法具有学习速度快、诊断精度高等优点,可用于通信线路及其他电子设备的噪声消除。
This article gave a method for adaptive noise cancellation based on ANFIS, and introduced the related theory and algorithm to make it come true. Meanwhile, it designed the ANFIS model by using the special function and some noise signals, distinguishing the parameters of the useful signal through the model. The emulation result shown that the method has many advantages, such as fast learning speed, high precision of distinguishing. So the method can be used in correspondence circuit and other electron equipment.
出处
《微计算机信息》
北大核心
2007年第05S期312-314,共3页
Control & Automation
基金
山西省自然科学基金(20051044)
关键词
自适应噪声消除
神经网络
自适应神经模糊推理系统
Adaptive Noise Cancellation, Neural Network, Adaptive-Network-Based Fuzzy Inference System