Digital modulation recognition based on wavelet nerual network
Zhou Jing-quan · Computer Knowledge and Technology · 2008
In this paper,tincture extraction method based on entropy is used to decrease computational times and strengthen the effectiveness of classification.At the same time,improved arithmetic is used to train WNN ,which effectively avoide getting into partial minimum values.It conquers the inherent flaw of conditional BP net,and improves training speed as well as ..The test shows that the system can recognize types of digital modulation signals.Application of this method to modulation recognition of practial signals shows satisfactory performance.