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	数控机床故障诊断专家系统开发与研究学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2012 张爱瑜收藏 \| 浏览/下载：69/0 \| 提交时间：2015/09/02 数控机床故障诊断专家系统故障树产生式表示小波包算法 BP神经网络正反向推理 CNC machine tool fault diagnosis expert system fault tree production rule wavelet packet algorithm BP neural network forward and backward reasoning
	A MLP-PNN neural network for CCD image super-resolution in wavelet packet domain (EI CONFERENCE) 会议论文 OAI收割 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, October 12, 2008 - October 14, 2008, Dalian, China Zhao X.; Fu D.; Zhai L. 收藏 \| 浏览/下载：68/0 \| 提交时间：2013/03/25 Image super-resolution methods process an input image sequence of a scene to obtain a still image with increased resolution. Classical approaches to this problem involve complex iterative minimization procedures typically with high computational costs. In this paper is proposed a novel algorithm for super-resolution that enables a substantial decrease in computer load. First decompose and reconstruct the image by wavelet packet. Before constructing the image use neural network in place of other rebuilding method to reconstruct the coefficients in the wavelet packet domain. Second probabilistic neural network architecture is used to perform a scattered-point interpolation of the image sequence data in the wavelet packet domain. The network kernel function is optimally determined for this problem by a MLP-PNN (Multi Layer Perceptron - Probabilistic Neural Network) trained on synthetic data. Network parameters dependent on the sequence noise level. This super-sampled image is spatially Altered to correct finite pixel size effects to yield the final high-resolution estimate. This method can decrease the calculation cost and get perfect PSNR. Results are presented showing the quality of the proposed method. 2008 IEEE.
	A method tor auto-extraction of spectral lines based on convolution type of wavelet packet transformation 期刊论文 OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 卷号: 26, 期号: 2, 页码: 372-376 作者: Liu, ZT; Wu, FC; Luo, AL; Zhao, YH 收藏 \| 浏览/下载：22/0 \| 提交时间：2015/11/07 convolution type of wavelet packet local correlation algorithm astronomical spectra spectral line extraction
	A method tor auto-extraction of spectral lines based on convolution type of wavelet packet transformation 期刊论文 OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 卷号: 26, 期号: 2, 页码: 372-376 作者: Liu, ZT; Wu, FC; Luo, AL; Zhao, YH 收藏 \| 浏览/下载：17/0 \| 提交时间：2017/03/14 convolution type of wavelet packet local correlation algorithm astronomical spectra spectral line extraction
	Wavelet packet and neural network basis medical image compression (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China Zhao X.; Wei J.; Zhai L. 收藏 \| 浏览/下载：20/0 \| 提交时间：2013/03/25 It is difficult to get high compression ratio and good reconstructed image by conventional methods we give a new method of compression on medical image. It is to decompose and reconstruct the medical image by wavelet packet. Before the construction the image use neural network in place of other coding method to code the coefficients in the wavelet packet domain. By using the Kohonen's neural network algorithm not only for its vector quantization feature but also for its topological property. This property allows an increase of about 80% for the compression rate. Compared to the JPEG standard this compression scheme shows better performances (in terms of PSNR) for compression rates higher than 30. This method can get big compression ratio and perfect PSNR. Results show that the image can be compressed greatly and the original image can be recovered well. In addition the approach can be realized easily by hardware.
	AE signal processing and DSP implementation based on wavelet packet analysis (EI CONFERENCE) 会议论文 OAI收割 ICMIT 2005: Information Systems and Signal Processing, September 20, 2005 - September 23, 2005, Changchun, China 作者: Zhao J.; Wang K. 收藏 \| 浏览/下载：13/0 \| 提交时间：2013/03/25 To improve the accuracy of AE (Acoustic Emission) testing the wavelet packet analysis was introduced to process the AE signals. Extraction of the fault characteristic information would be influenced greatly if the faulted AE signal was not effectively denoised. Based on discussing the fast searching algorithm of BWPB (Best Wavelet Packet Basis) adopting Shannon entropy a new method based on BWPB was presented to denoise the AE signal from the faulted composite plate. Analyzing was performed on the denoised signal and the fault characteristic information was exacted. To improve the real-time performance of the wavelet packet analysis algorithm it was performed on the DSP (Digital Signal Processing) chip TMS320VC5409. The experimental results show that the algorithm can not only reduce the noise by 10dB but also effectively extract the faulted characteristics information from the AE signal.