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matching pursuit-based tap selection technique for UWB channel equalization

IEEE COMMUNICATIONS LETTERS 2005年第9期9卷 835-837页

作者： Lin, ZW Premkumar, AB Madhukumar, AS Nanyang Technol Univ Sch Comp Engn Singapore 2263 Singapore

In this letter, matching pursuit (MP) based tap selection technique is proposed and applied to Ultra Wideband (UWB) indoor channel equalization in the presence of Inter Symbol Interference (ISI) and Multiple Access Interference (MAI). Given the limited training sample support, quadratic constraint is incorporated into MP algorithm to insure the robustness for tap selection. The proposed method is shown to outperform the conventional Minimum Mean Square Error (MMSE) equalizer significantly given the same amount of training symbols.

关键词： ultra wideband (UWB) matching pursuit algorithm tap selection

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Direction of arrival estimation using matching pursuit under reverberant condition

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ACOUSTICAL SCIENCE AND TECHNOLOGY 2005年第4期26卷 365-367页

作者： Oikawa, Yasuhiro Yamasaki, Yoshio Waseda Univ Global Informat & Telecommun Inst 1011 Okuboyama Nishi Tomida Honjo 3670035 Japan

The method for estimating the direction of arrival (DOA) using a matching pursuit algorithm under reverberant conditions is discussed. The method starts with the obtaining of an array output of the delay-and-sum method and calculating the average array output in the fixed frequency range. The DOA is estimated by iteration at each step and a re-optimization of all DOA found at the earlier steps. It is suggested that the method can be improved by considering the spatial information from this method.

关键词： DOA estimation matching pursuit algorithm Delay-and-Sum array DOA re-optimization

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Adaptive coding using matching pursuit in MRI

Adaptive coding using matching pursuit in MRI

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Medical Imaging 1998 Conference on Image Processing

作者： Ro, YM Chung, JY Informat & Commun Univ Sch Commun Engn Yusong Gu Taejon 305350 South Korea

ISBN: (纸本)0819427837

An adaptive coding is proposed for magnetic resonance (MR) imaging. In this paper, we propose an adaptive coding using the matching pursuit algorithm to the MR imaging. The matching pursuit algorithm is performed with the dictionary consisting windowed Fourier basis set to achieve adaptive coding. Image domain is segmented into several groups. Since the image signal is divided into small scale, the matching pursuit with the segmented signal is more effective than that with whole image domain. Since matching pursuit is a greedy algorithm to find waveforms which are the best match for an object signal, the signal can be decomposed with a few iterations thereby resulting reduction of imaging time. Computer simulations and experiments are performed to verify the proposed technique.

关键词： adaptive phase encoding windowed Fourier transform matching pursuit algorithm

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Fuzzy systems identification with orthogonal matching pursuit

Fuzzy systems identification with orthogonal matching pursui...

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5th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 96)

作者： Shmilovici, A Maimon, O TEL AVIV UNIV DEPT IND ENGNIL-69978 TEL AVIVISRAEL

ISBN: (纸本)0780336461

A recursive algorithm is described for computing the representation of functions with respect to a nonorthogonal and possibly overcomplete dictionary of elementary building blocks. This algorithm, which follows the Orthogonal matching pursuit algorithm, is used for the identification of fuzzy systems where the membership functions are the basic building blocks. The algorithm is demonstrated on the identification of the Glycolytic chaotic time series.

关键词： matching pursuit algorithm fuzzy systems identification problem

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Automatic Epileptic Seizure Onset Detection Using matching pursuit: A Case Study

Automatic Epileptic Seizure Onset Detection Using Matching P...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Sorensen, Thomas L. Olsen, Ulrich L. Conradsen, Isa Henriksen, Jonas Kjaer, Troels W. Thomsen, Carsten E. Sorensen, Helge B. D. Tech Univ Denmark Dept Elect Engn Lyngby Denmark Rigshospitalet Univ Hosp Dept Clin Neurophysiol Copenhagen Denmark Univ Copenhagen Dept Odontol Copenhagen Denmark

ISBN: (纸本)9781424441242

An automatic alarm system for detecting epileptic seizure onsets could be of great assistance to patients and medical staff. A novel approach is proposed using the matching pursuit algorithm as a feature extractor combined with the Support Vector Machine (SVM) as a classifier for this purpose. The combination of matching pursuit and SVM for automatic seizure detection has never been tested before, making this a pilot study. Data from red different patients with 6 to 49 seizures are used to test our model. Three patients are recorded with scalp electroencephalography (sEEG) and three with intracranial electroencephalography (iEEG). A sensitivity of 78-100% and a detection latency of 5-18s has been achieved, while holding the false detection at 0.16-5.31/h. Our results show the potential of matching pursuit as a feature extractor for detection of epileptic seizures.

关键词： SVM classifier automatic alarm system automatic epileptic seizure onset detection diseases electroencephalography feature extraction feature extractor intracranial electroencephalography iterative methods matching pursuit algorithm medical signal detection medical signal processing scalp electroencephalography signal classification support vector machine support vector machines

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Automated detection of sleep EEG slow waves based on matching pursuit using a restricted dictionary

Automated detection of sleep EEG slow waves based on matchin...

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33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS)

作者： Picot, Antoine Whitmore, Harry Chapotot, Florian Univ Chicago Sleep Metab & Hlth Ctr Chicago IL 60642 USA

ISBN: (纸本)9781424441228

In this paper, an original method to detect sleep slow waves (SSW) in electroencephalogram (EEG) recordings is proposed. This method takes advantage of a matching pursuit algorithm using a dictionary reduced to Gabor functions reproducing the main targeted waveform characteristics. By describing the EEG signals in terms of SSW properties, the corresponding algorithm is able to identify waveforms based on the largest matching coefficients. The implemented algorithm was tested on a database of whole night sleep EEG recordings collected in 9 young healthy subjects where SSW have been visually scored by an expert. Besides being fully automated and much faster than visual scoring analysis, the results obtained to the proposed method were in excellent agreement with the expert with 98% of correct detections and a 77% concordance in event time position and duration. These results were superior from those of the classical method both in terms of sensibility and precision.

关键词： Databases Dictionaries Electroencephalography Gabor filters Gabor function Humans matching pursuit algorithms Oscillators Sleep automated detection electroencephalogram recording electroencephalography iterative methods matching pursuit algorithm medical

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PZT transducer array enabled pipeline defect locating based on time-reversal method and matching pursuit de-noising

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SMART MATERIALS AND STRUCTURES 2019年第7期28卷 075019-075019页

作者： Xu, Yang Luo, Mingzhang Liu, Qiang Du, Guofeng Song, Gangbing Yangtze Univ Jingzhou 434023 Hubei Peoples R China Yangtze Univ Natl Demonstrat Ctr Expt Electrotech & Elect Educ Jingzhou Hubei Peoples R China CNPC Tubular Goods Res Inst Xian 710077 Shaanxi Peoples R China Univ Houston Dept Mech Engn Houston TX 77204 USA

In the process of pipeline structural health monitoring, it is necessary to detect pipe defects as well as to locate the defect's axial and circumferential positions. Axial locating of a pipeline defect can be achieved by identifying the defect reflection packets in the direct detected axial displacement time history signals. In practice, various kinds of noise are involved in the actual detection signal. Using the matching pursuit (MP) algorithm based on a custom over-complete waveform dictionary, the noisy detection signal can be effectively de-noised, and the defect's axial position can be located. The time-reversal method used in a waveguide leads to temporal and spatial focusing, and this feature is used to locate the defect's circumferential position in the pipeline. In this paper, a new pipeline defect locating approach based on the time-reversal method and MP de-noising is proposed. The integration of the finite element method (FEM) numerical simulation with experiment is utilized to locate the pipeline defect. The defect axial position L-x is located by the direct detected signal obtained from the actual pipeline defect detection experiment, after MP de-noising. A defect-free FEM reference model is established, and it has the same geometric and material parameters as the actual pipeline. Re-generating the time reversed defect reflection and the converted mode signals in the reference model, the energy will focus on the L-x position. After obtaining the maximum values of the axial displacement time history signals received from the reference model at the L-x position, the polar coordinate map based on these maxima can be plotted. The defect circumferential position is located based on the maximum values on the map. The FEM numerical simulation and experimental results are performed in this research. The defect locating results agree well with the actual pipeline defects, in both the axial and the circumferential directions.

关键词： ultrasonic guided wave matching pursuit algorithm time-reversal method lead zirconate titinate (PZT) pipeline defect signal de-noising

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Statistical models of sets of curves and surfaces based on currents

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MEDICAL IMAGE ANALYSIS 2009年第5期13卷 793-808页

作者： Durrleman, Stanley Pennec, Xavier Trouve, Alain Ayache, Nicholas INRIA Sophia Antipolis Asclepios Team Project F-06902 Sophia Antipolis France ENS Cachan Ctr Math & Leurs Applicat F-94235 Cachan France

Computing, visualizing and interpreting statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computer graphics. Modeling such geometrical primitives with currents avoids to base the comparison between primitives either on a selection of geometrical measures (like length, area or curvature) or on the assumption of point-correspondence. This framework has been used relevantly to register brain surfaces or to measure geometrical invariants. However, while the state-of-the-art methods efficiently perform pairwise registrations, new numerical schemes are required to process groupwise statistics due to an increasing complexity when the size of the database is growing. In this paper, we propose a matching pursuit algorithm for currents, which allows us to approximate. at any desired accuracy, the mean and modes of a population of geometrical primitives modeled as currents. This leads to a sparse representation of the currents, which offers a way to visualize. and hence to interpret, such statistics. More importantly, this tool allows us to build atlases from a population of currents, based on a rigorous statistical model. In this model, data are seen as deformations of an unknown template perturbed by random currents. A Maximum A Posteriori approach is used to estimate consistently the template, the deformations of this template to each data and the residual perturbations. Statistics on both the deformations and the residual currents provide a complete description of the geometrical variability of the structures. Eventually, this framework is generic and can be applied to a large range of anatomical data. We show the relevance of our approach by describing the variability of population of sulcal lines, surfaces of internal structures of the brain and white matter fiber bundles. Complementary experiments on simulated data show the potential of the method to give anatomical characterization of patholog

关键词： Currents Curves Surfaces Statistics matching pursuit algorithm Approximation Sparse decomposition Atlas estimation Template Registration Shape space Anatomical variability Group classification Computational anatomy

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Sparse/dense channel estimation with non-zero tap detection for 60-GHz beam training

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IET COMMUNICATIONS 2014年第11期8卷 2044-2053页

作者： Gao, Bo Xiao, Zhenyu Zhang, Changming Jin, Depeng Zeng, Lieguang Tsinghua Univ Dept Elect Engn State Key Lab Microwave & Digital Commun Beijing 100084 Peoples R China Beihang Univ Sch Elect & Informat Engn Beijing 100191 Peoples R China

Estimation of the multipath channel in 60-GHz communications is challenging, because the channel may be sparse or dense during beam training. Specifically, because of the variation of the number of non-zero taps, it is hard for common estimators to obtain robust and prominent performance. In order to address this problem, the authors propose a sparse/dense channel estimation with non-zero tap detection (SDCE-NTD). The estimation is conducted in a three-stage fashion, including initial estimation with the unstructured least-square (LS) algorithm, non-zero-tap detection with the generalised likelihood ratio test approach, and posterior estimation with the structured LS algorithm. The false-alarm and detection probability of the tap detector, as well as the mean square error (MSE) of SDCE-NTD, are derived and confirmed via simulations. Comparisons are conducted between SDCE-NTD and the common estimators in the beam training scenarios, where both dense and sparse channels exist. Results show that SDCE-NTD reveals a significant gain in terms of MSE over both the conventional LS algorithm, which does not exploit the sparse nature of the channel, and the matching pursuit algorithm, which endeavours to exploit the sparsity. In addition, it is also demonstrated that the proposed estimator can approach the lower bound with high signal-to-noise ratio.

关键词： channel estimation multipath channels least squares approximations probability mean square error methods frequency 60 GHz matching pursuit algorithm MSE mean square error detection probability false-alarm probability posterior estimation generalised likelihood ratio test approach LS algorithm unstructured least-square algorithm SDCE-NTD multipath channel estimation beam training nonzero tap detection sparse-dense channel estimation

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An adaptive fault detection method based on atom sparse and evidence fusion for the small current to ground system

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2018年第5期40卷 1579-1592页

作者： Wang, Xiaowei Wei, Xiangxiang Yang, Dechang Gao, Jie Sun, Xue Song, Guobing Xi An Jiao Tong Univ Sch Elect Engn Xian Shanxi Peoples R China China Agr Univ Coll Informat & Elect Engn Beijing 100083 Peoples R China Shanghai Univ Elect Power Coll Automat Engn Shanghai Peoples R China

An adaptive fault detection method for the small current to ground system is proposed based on the atom sparse and evidence fusion theory. Firstly, the two cycles of transient zero-sequence current are obtained when occur fault, which is decomposed by the matching pursuit algorithm, and the iterations are set to four, then, according to the correlation analysis, the best three atoms of maximum correlation are chosen and which are sorted by the correlation coefficients. Secondly, we obtained the determine fault measure (DFM) values by calculating the atomic energy entropy, and selected the atomic fault trust (FT) function by revising the DFM. Finally, the FT values are integrated by the D-S (Dempster-Shafer) evidence theory, then the fault comprehensive trust values are gained, the selection results are output. Simulation results show that the method of fault line detection is accurate and reliable.

关键词： Fault detection matching pursuit algorithm correlation analysis fault trust function energy entropy D-S evidence theory

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