@inproceedings{398f7fe7a0284e2ca41f6697c006935d,
title = "Application of self-adaptive wavelet neural networks in ultrasonic detecting",
abstract = "It is important to remove the noise signal effectively in non-destructive testing. Using the wavelet and neural network algorithm, the author constructed self-adaptive wavelet neural networks in the ultrasonic testing. Better fitting signal is achieved by choosing Orthogonal Daubechies wavelet neuron and optimized scale parameter. The simulation results showed less distortion and better noise cancellation, and the method can be widely applied ton ultrasonic detecting.",
keywords = "Neural networks, Self-adaptive, Ultrasonic, Wavelet analysis",
author = "Yin, {Xi Peng} and Fan, {Yang Yu} and Duan, {Zhe Min} and Wei Cheng",
year = "2009",
doi = "10.1109/ICASID.2009.5276998",
language = "英语",
isbn = "9781424438839",
series = "2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication, ASID 2009",
publisher = "IEEE Computer Society",
pages = "600--602",
booktitle = "2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication, ASID 2009",
note = "2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication, ASID 2009 ; Conference date: 20-08-2009 Through 22-08-2009",
}