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USING SUB-BAND RECONSTRUCTION IN WAVELET SPACE AND FOURIER TRANSFORM TO EXTRACT LOCAL FEATURES FROM ANALYTICAL SIGNALS EXACTLY AND STRAIGHTFORWARDLY

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ANALYTICAL LETTERS 2010年第6期43卷 1019-1032页

作者： Tang, Li-Juan Jiang, Jian-Hui Wu, Hai-Long Shen, Guo-Li Yu, Ru-Qin Hunan Univ Coll Chem & Chem Engn State Key Lab Chemo Biosensing & Chemometr Changsha 410082 Hunan Peoples R China

To cope with the problem of frequency aliasing in mallat algorithm, which makes traditional discrete wavelet transform (DWT) inappropriate for feature extraction in some cases, an improved algorithm composed of sub-band reconstruction and Fourier transform is suggested through which the original signal could be split into a series of sub-bands of different frequencies with little distortion both in time and frequency domains. This strategy is developed to extract local features from analytical signals accurately as well as straightforwardly. Some NIR spectra have been selected as examples to demonstrate the availability and application of the proposed method.

关键词： Discrete wavelet transform (DWT) Feature extraction Fourier transform Frequency aliasing mallat algorithm Near-infrared spectroscopy (NIR) Sub-band reconstruction

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Detection of ECG Characteristic Points Using Biorthogonal Spline Wavelet

Detection of ECG Characteristic Points Using Biorthogonal Sp...

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2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI 2010)

作者： Pan, Tao Zhang, Lei Zhou, Shumin Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China

ISBN: (纸本)9781424464968

An algorithm based on Biorthogonal Spline Wavelet is developed for detecting ECG characters points. In the algorithm, the Biorthogonal Spline Wavelet Transform of the ECG signal is first calculated using mallat algorithm. And then the R-peak is located by finding the best modulus maximum pair of the wavelet transform in the scale of 2(3). A more robust method to find the modulus maximum pair is put forward in this paper. The methods finding the onsets and offsets of QRS complexes, P and T waves are also provided. The detection rate of QRS complexes for the algorithm is above 99.7% for MIT/BIH database and the processing time is considerably little.

关键词： ECG detection Wavelet transform mallat algorithm

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Research of Still Image Compression Based on Daubechies 9/7 Wavelet Transform

Research of Still Image Compression Based on Daubechies 9/7 ...

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The 2010 2nd International Conference on Future Computer and Communication(第二届未来计算机与通信国际会议 ICFCC 2010)

作者： Qiu-yuan CAI Geng-sheng WANG Yun-xin YU School of Information Engineering .East China Jiaotong University Nanchang 330013China

ISBN: (纸本)9781424458219;9781424458240

The application of Wavelet-based still image compression is becoming more and more perfect as the wavelet theory research proceeds in latest *** on the analysis of the basic theory of wavelet transform, the application of wavelet transform is studied in still image compression, and implement the Daubechies 9/7 wavelet transform of three decomposition by using the VC++ platform *** experimental results are given in the corresponding part of the reconstructed image and compression ratio and PSNR values.

关键词： wavelet transform multi-resolution analysis mallat algorithm Daubechies(9,7)wavelet image compression

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Wave-Based Financial Data Processing and Empirical Analysis

Wave-Based Financial Data Processing and Empirical Analysis

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2010年中国通信国际会议

作者： Jie TANG1,Xijun CHENG2 1 Department of Management Science and Engineering 2 Department of Statistics and Finance University of Science and Technology of China,USTC,Hefei,China

This paper takes financial data as one-dimensional random signal and uses wavelet mallat algorithm to denoise the original signal in order to get a more accurate signal which fits market situation *** the empirical analysis,this paper applies closing price of Baoshan Iron and Steel shares for example to verify the capacity of wavelet multi-resolution analysis on financial data processing,and the result is satisfactory.

关键词： wavelet multi-resolution mallat algorithm signal de-noising

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The prediction of oil quality based on Least Squares Support Vector Machines and Daubechies wavelet and mallat algorithm

The prediction of oil quality based on Least Squares Support...

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6th International Conference on Intelligent Systems Design and Applications (ISDA 2006)

作者： Li Fangfang Zhao Yingkai Jiang ZhiBing Nanjing Univ Technol Dept Automat Xuzhou Jiangsu Prov Peoples R China Nanjing Univ Technol Dept Automat Zhenjiang Jiangsu Prov Peoples R China Nanjing Univ Technol Dept Automat Nantong Jiangsu Prov Peoples R China

ISBN: (纸本)0769525288

Support Vector Machines (SVM) is a new type of machine learning algorithm. Compared with conventional learning algorithms, SVM enhances the generalization ability of the models by employing structural risk minimization criterion to minimize the sample errors and simultaneously decrease the upper bound of the predict error of the models. The global optimal solution can be uniquely obtained owing to that SVM converts machine learning into quadratic programming. Based on the local data from hydrogenation equipment, a predictive model using Least Squares Support Vector Machines (LS-SVM) is established for three important quality targets of diesel oil in this paper, and compared with neural network and stands SVM on precision. Finally, it is proved that the proposed predictive models based on LS-SVM can predict the quality target more efficiently and rapidly than stands SVM and neural network. It provided a method for online diagnosing fault of quality targets.

关键词： Least Squares Vector Machines (LS-SVM) prediction oil quality Daubechies wavelet mallat algorithm

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Application of Wavelet Transform in Vehicle Speed Signal Denoising

Application of Wavelet Transform in Vehicle Speed Signal Den...

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International Conference on Measuring Technology and Mechatronics Automation

作者： Wang, Hai Zhang, Weigong Southeast Univ Sch Instrument Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9780769535838

Wheel speed is a critical parameter in vehicle roadway test. However, because of the internal defects of the wheel speed sensor structure and some electromagnetic inference, this signal is inevitably influenced by kinds of awful noises during the measurement process. These wide band stochastic noises badly influence the analysis of vehicle performance. It is difficult to eliminate these noises with traditional way based on Fourier transform. Wavelet transform is an analytical method of time-frequency, which is especially suitable for the analysis of non-stable signals. This method contains a characteristic of multi-resolution analysis as well as the ability of identifying partial characteristics of signals in time-frequency domain. According to different characteristics of signals and noises at every scale spaces after wavelet transform, the method of soft-threshold is applied to eliminate the noises in this paper. The result suggests this method is effective in wheel speed signal denoising.

关键词： wheel speed signal wavelet transform multi-resolution analysis soft-threshold mallat algorithm

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A new discrete wavelet transform fast algorithm with rational dilation factor

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INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING 2008年第4期6卷 609-616页

作者： Li, Hui-Guang Li, Yan Sun, Chang-Pin Li, Xiao-Li Yanshan Univ Inst Elect Engn Qinhuangdao Hebei Peoples R China Univ Birmingham Sch Comp Sci CERCIA Birmingham B15 2TT W Midlands England

While in the process of decomposition of the mallat discrete wavelet transform (DWT) fast algorithm, the algorithm has a drawback, that is, there is frequency distortion in the high frequency subband. In this paper, a new algorithm of decomposition and reconstruction in the discrete wavelet is presented. The algorithm can solve the frequency distortion in the high frequency subband in the process of decimation in each level. The simulation of numerical value example tests the validity of the algorithm.

关键词： rational multiresolution analysis rational filter banks mallat algorithm rational wavelet frequency distortion

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Speckle noise reduction in SAS imagery

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SIGNAL PROCESSING 2007年第4期87卷 762-781页

作者： Chaillan, Fabien Fraschini, Christophe Courmontagne, Philippe ISEN Dept Phys Maison Technol F-83000 Toulon France

Synthetic aperture sonar (SAS) is actively used in sea bed imagery. Indeed high resolution images provided by SAS are of great interest, especially for the detection, localization and eventually classification of objects lying on sea bed. SAS images are highly corrupted by a granular multiplicative noise, called speckle noise which reduces spatial and radiometric resolutions. The purpose of this article is to present a new adaptive processing that allows image filtering, for both the additive and multiplicative noise case. This new process is based on the marriage between a multi-resolution transformation and a filtering method. The filtering technique used here is based on the two-dimensional stochastic matched filtering method, which maximizes the signal-to-noise ratio after processing and minimizes mean square error between the signal's approximation and the original one. Results obtained on real SAS data are presented and compared with those obtained using classical processing. (c) 2006 Elsevier B.V. All rights reserved.

关键词： SAS images speckle stochastic matched filter multi-resolution analysis mallat algorithm

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Fractal scale descriptors based on 3d wavelet moments for 3d objects

Fractal scale descriptors based on 3d wavelet moments for 3d...

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5th International Conference on Wavelet Analysis and Pattern Recognition

作者： Cui, Li Li, Ying Xu, Dong Li, Him Beijing Normal Univ Sch Math Sci Beijing 100875 Peoples R China Tsinghua Univ State Key Lab Intelligent Technol & Syst Dept Comp Sci & Technol Beijing 100084 Peoples R China Jilin Univ Coll Comp Sci & Technol Changchun 130021 Peoples R China Chinese Acad Sci Inst Comp Technol Natl Res Ctr Intelligent Comp Syst Beijing 100080 Peoples R China Grad Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9781424410651

In this paper based on 3d wavelet moments we present a new method called fractal scale descriptors for 3d objects. Just like wavelet moments, they are still robust to translation, rotation and scale, and have the multi-resolution features in the radial direction, which can handle noise to some extent and provide multi-level features to satisfy, various requirements. Furthermore the new method is prior to the original 3d wavelet moments in computational complexity by using the fast algorithm of the spherical harmonics together with the mallat algorithm of the wavelets.

关键词： fractal scale wavelet moments mallat algorithm spherical harmonics

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A new discrete wavelet transform fast algorithm with rational dilation factor

A new discrete wavelet transform fast algorithm with rationa...

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5th International Conference on Wavelet Analysis and Pattern Recognition

作者： Li, Hui-Guang Sun, Chang-Ping Li, Yang Li, Xiao-Li Yanshan Univ Inst Elect Engn Qinhuangdao 066004 Peoples R China

ISBN: (纸本)9781424410651

While in the process of decomposition of the mallat discrete wavelet transform(DWT) fast algoritm, the algorithm have a drawback, that is, there is frequency distortion in the high frequency subband In this paper, a new discrete wavelet decomposition and reconstruction algorithm is presented The algorithm can solve the frequency distortion in the high frequency subband in the process of decimation in each level. The simulation of numerical value example had verified the validity of the algorithm.

关键词： rational multi resolution analysis rational filter banks mallat algorithm rational wavelet frequency distortion

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