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	Identify fine microstructure of multifarious iron oxides via O K-edge EELS spectra 期刊论文 OAI收割 CHINESE CHEMICAL LETTERS, 2022, 卷号: 33, 期号: 9, 页码: 4375-4379 作者: Chen, Junnan; Li, Yujie; Lu, Ming; Niu, Yiming; Zhang, Bingsen \| 收藏 \| 浏览/下载：56/0 \| 提交时间：2022/09/16 EELS ELNES EXELFS Transition metal oxides DFT Wavelet analyze
	Information extraction from laser speckle patterns using wavelet entropy techniques (EI CONFERENCE) 会议论文 OAI收割 MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, November 4, 2011 - November 6, 2011, Guilin, China 作者: Li X.-Z.; Wang X.-J. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 A novel speckle patterns processing method is presented using multi-scale wavelet techniques. Laser speckle patterns generated from the sample contained abundant information. In this paper we propose a method using wavelet entropy techniques to analyze the speckle patterns and exact the information on the sample surface. In our case we used this approach to test the solar silicon cell surface profiles based on the sym8 orthogonal wavelet family. According different wavelet entropy values the micro-structure of different solar silicon cell surfaces were comparative analyzed. Furthermore we studied the AFM and reflective spectra of the wafer. Results show that the wavelet entropy speckle processing method is effective and accurate. And the experiment proved that this method is a useful tool to investigate the surface profile quality. 2011 SPIE.
	A new approach for the removal of mixed noise based on wavelet transform (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：35/0 \| 提交时间：2013/03/25 This paper proposed a new approach for the removal of mixed noise. There are many different ways in image denoising. Donoho et al have proposed a method for image de-noising by thresholding ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In the light and indeed we combine the merits of the two techniques to form a new approach for the removal of mixed noise. At first the application of their method to image denoising has been extremely successful. But the method of Donoho is based on the assumption that the type of noise is only additive Gaussian noise we used wavelet singularity detection (WSD) technique to analyze singularities of signal and noise. According to the characteristic that wavelet transform modulus maxima of impulse noise rapidly decreases as the scale increases in wavelet domain which is not successful for impulse noise. Mallat has also presented a method for signal denoising by discriminating the noise and the signal singularities through an analysis of their wavelet transform modulus maxima (WTMM). Nevertheless it can be accurately located with multiscale space by going through dyadic orthogonal wavelet transform and removed. Furthermore the Gaussian noise is also removed through a level-dependent thresholding algorithm the tracing of WTMM is not just tedious procedure computationally algorithm. The experimental results demonstrate that the proposed method can effectively detect impulse noise and remove almost all of the noise while preserve image details very well.
	The signal extraction of fetal heart rate based on wavelet transform and BP neural network (EI CONFERENCE) 会议论文 OAI收割 Third International Conference on Experimental Mechanics and Third Conference of the Asian Committee on Experimental Mechanics, November 29, 2004 - December 1, 2004, Singapore, Singapore Hong Y. X.; Cheng Z. B.; Dai F. H. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 This paper briefly introduces the collection and recognition of bio-medical signals the other threading is analyzing data. Using the method designs the method to collect FM signals. A detailed discussion on the system hardware it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network structure and functions is also given. Under LabWindows/CVI Finally the results of collecting signals and BP networks are discussed.8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure. the hardware and the driver do compatible the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively expedites program reflect speed improves the program to perform efficiency. One threading is collecting data