摘要
研究了用自联想网络(AANN)进行数字滤波的方法。自联想网络采用一种带有瓶颈层的特殊结构,且具有单位总增益。在经过大量带噪声样本的训练之后,各变量之间能够建立起内在联系。输入信息通过瓶颈层前的压缩及瓶颈层后的解压缩过程,信息中的精华将被提取,从而使人们能够利用冗余信息抑制其测量噪声,使发动机测量参数在最大程度上减少噪声对其带来的负面影响。
The method of digital filtering by auto-associative neural network (AANN) is studied. The AANN adopts a special structure with abottle-nect layer and has an unit overall gain. The internal relation between the variables can be built after the training of a large amount of noise samples. The quintessence of the information can be extracted through the compression before the bottle-nect layer and the decompression after that. And then the redundant information can be used to restrain the noise during the measurement. The negtive effect of the noise upon the paramenter measurement of the aero-engine can be reduced maximally.
出处
《计测技术》
2005年第2期14-16,共3页
Metrology & Measurement Technology
关键词
自联想网络
航空发动机
噪声
数字滤波
aero-engine
auto-associative neural network
noise
digital filtering
