An RBFN-Wiener hybrid filter using higher order signal statistics
An RBFN-Wiener hybrid filter using higher order signal statistics
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DOI：
10.1016/j.asoc.2006.04.005
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发表时间：
2007-06-01
影响因子：
8.7
通讯作者：
Uchino, Eiji
中科院分区：
文献类型：
--
作者：
Suetake, Noriaki;Uchino, Eiji
在本文中，我们提出了一种基于径向基函数网络（RBFN）的非线性滤波器，其基本框架为线性维纳滤波器。此外，为了提高滤波性能，我们进一步提出了一种新颖的非线性滤波器，它是由 RBFN 滤波器和线性维纳滤波器混合而成。所提出的滤波器是利用目标信号和观测噪声的高阶统计量以最小均方误差方案来实现的。所提出的滤波器的有效性和有效性已通过将其应用于噪声图像的实际滤波问题来验证。 (c) 2006 Elsevier B.V. 保留所有权利。
In this paper we propose a radial basis function network ( RBFN) based nonlinear filter with a basic framework of a linear Wiener filter. In addition, in order to improve the filtering performance, we further propose a novel nonlinear filter, which is synthesized by a hybridization of an RBFN filter and a linear Wiener filter. The proposed filters are realized with a least mean square error scheme using higher order statistics of a target signal and an observation noise.The validity and the effectiveness of the proposed filters have been verified by applying them to the actual filtering problems of the noisy images. (c) 2006 Elsevier B. V. All rights reserved.