Detection of weak signals Based on RBF Neural Network filtering

被引：0
|
作者：
Li Jian-jun [1 ]
机构：
[1] Inner Mongolia Sci & Technol Univ, Informat Engn Coll, Baotou 014010, Peoples R China
来源：
MECHATRONICS AND INTELLIGENT MATERIALS, PTS 1 AND 2 | 2011年 / 211-212卷
关键词：
Neural Network; adaptive filter; Noise Cancellation; RBF; NATURAL GRADIENT; SYSTEMS;
D O I：
10.4028/www.scientific.net/AMR.211-212.846
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The algorithm is presented in this paper based on the character about RBF adaptive neural network filtering needn't previous information of input single and noise and has better ability of nonlinear mapping and self-study. The adaptive noise cancellation system is designed. The system can improve LMS algorithm slow convergence speed and extraction of narrow band signal faults and has small amount of calculation and real-time good characteristic. The effect is better at Using this system in the field of life characteristic signal detection identification. Results show that the system has the high feasibility and validity.
引用
收藏
页码：846 / 849
页数：4
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