摘要
提出了一种基于神经-模糊网络的自适应滤波器,它具有非线性映射和自学习能力,能够用于噪声信号的非线性建模。它不仅能够获取信号的最佳估计,并且能够克服信号处理中存在的模型和有色噪声的不确定性、不完备性。通过对仿真结果分析表明,提出的算法具有可靠、计算简便、快速等特点,模型滤波精度较高,并可实现实时滤波,具有一定的理论价值和实用价值。
This article gives a method for adaptive filter based on ANFIS.It is of both the ability of nonlinear mapping and the ability of self-studying,and could be used to achieve the non-linear model of noise.It could achieve the optimal estimation and overcome the uncertainty and incompleteness of signal model and colored noise.The simulation resultindicates that the algorithm proposed in this article is reliable,simple and fast,the model is of high filtering accuracy,and could realize real-time filter,and thus has certain value for both theory and practice.
出处
《信息安全与通信保密》
2010年第3期69-71,共3页
Information Security and Communications Privacy
