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pre-processing method for pitch smoothing

ELECTRONICS LETTERS 2001年第21期37卷 1314-1316页

作者： Farsi, H Kondoz, A Univ Surrey Ctr Commun Syst Res Multimedia Res Grp Surrey GU2 7XH England

A new pre-processing method for pitch smoothing is proposed. This methodology modifies the residual speech signal such that the pitch period evolves more smoothly without distorting perceptual speech quality. Thus, pitch can be effectively interpolated and transmitted only once per frame while presenting the long-term correlation of speech signal and maintaining the perceptual speech quality.

关键词： interpolation speech coding smoothing methods Speech and audio coding perceptual speech quality residual speech signal waveform interpolation pre-processing method pitch smoothing

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pre-processing method minimizing the need for reference analyses

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JOURNAL OF CHEMOMETRICS 2001年第2期15卷 123-131页

作者： Hansen, PW Foss Elect AS DK-3400 Hillerod Denmark

A new pre-processing method called independent interference reduction (IIR) is proposed. It is based on modelling of the interferences by use of principal component analysis (PCA) using samples containing no variation in the parameter of interest. This is followed by subtraction of the modelled effects from the calibration matrix. It is useful in cases where the parameter of interest gives only minor contributions to the calibration matrix and where, at the same time, samples not containing variation in this parameter are easy to obtain. In such a case the method reduces the number of reference analyses required for establishing a reliable calibration. When applied to acetone determination in milk samples by use of Fourier transform infrared (FT-III) spectroscopy, the method provides a treatment of the data which yields more stable models in the subsequent calibration step. Copyright (C) 2000 John Wiley & Sons, Ltd.

关键词： pre-processing method independent interference reduction infrared spectroscopy reference analysis

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A pre-processing method of internal thermal mass for building energy simulation software

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JOURNAL OF BUILDING PERFORMANCE SIMULATION 2021年第3期14卷 328-342页

作者： Li, Weilin Yang, Liu Zhu, Jiayin Li, Ruixin Zhengzhou Univ Sch Civil Engn Sci Ave 100 Zhengzhou 450001 Peoples R China Hong Kong Polytech Univ Dept Bldg Serv Engn Hong Kong Peoples R China

It is challenging to accurately establish the dynamic heat transfer model of the internal thermal mass owing to the irregular shape. In building energy simulation software, the internal thermal mass is described as slabs. However, the parameter setting of the equivalent slabs depends primarily on the user experience, which may lead to uncontrollable errors. Therefore, this paper proposes a method, termed the effective area method (EAM), which specifies the transformation of an irregular internal thermal mass to the slab and can be used as a pre-processing method for building simulation software. This paper describes the methodology and pre-processing logic of the EAM, and the implementation of the approach in EnergyPlus considering an office environment. The root-mean-square errors between the simulation and measured temperatures are less than 0.3 degrees C, which indicates that the EAM can effectively eliminate the errors caused by the unreasonable settings of the internal thermal mass.

关键词： Internal thermal mass EnergyPlus effective area method (EAM) pre-processing method

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AOTF based Molecular Hyperspectral Imaging System and Its Image pre-processing method 8

AOTF based Molecular Hyperspectral Imaging System and Its Im...

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8th International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Gao, Yunfeng Zhou, Mei Li, Qingli Liu, Hongying Zhang, Yang East China Normal Univ Shanghai Key Lab Multidimens Informat Proc Shanghai 200241 Peoples R China

ISBN: (纸本)9781509000227

Utilizing both spectral and spatial information, hyperspectral images provide more detail than the single point spectroscopy or traditional images. With the improvement of hyperspectral imaging instrumentation, hyperspectral data analysis techniques are getting more attention. However, desired analysis and results depend strongly on the quality of image pre-processing. In this paper, we obtained hyperspectral images through an Acousto-Optic Tunable Filter (AOTF) based molecular hyperspectral imaging (MHI) system. Then the Lambert-Beer law based pre-processing method was presented to calibrate molecular hyperspectral images. This method combines the advantages of spectral correction and spatial denoising. We applied K-Means classification algorithm and IsoData classification algorithm to the preprocessed blood cell images and the experimental results prove the performance of the pre-processing method which is useful for the further classification.

关键词： hyperspectral images pre-processing method molecular hyperspectral imaging (MHI) system Lambert-Beer law

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Rolling ball method applied to 31/21/2-axis machining for tool orientation and positioning and path planning

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ADVANCES IN MECHANICAL ENGINEERING 2015年第12期7卷 1-12页

作者： Roman, Armando Barocio, Eduardo Huegel, Joel C. Bedi, Sanjeev Tecnol Monterrey Col Nvo Mexico 45210 Zapopan Mexico Purdue Univ Dept Mat Engn W Lafayette IN 47907 USA Univ Waterloo Automat & Control Grp Waterloo ON N2L 3G1 Canada

In 31/21/2-axis machining, the machined part surface is partitioned in pre-processing in order to calculate the tool position and patch boundaries and then machined in patches, thereby minimizing the intermediate manual part re-positioning and the overall machining time. Each patch requires a constant, but different, tool orientation. In previous research, local properties have been used to subdivide surfaces into patches. For an ideal tool position and orientation, however, the tool's shape and curvature should exactly match the shape and curvature of the part surface. The rolling ball method, originally developed for 5-axis machining, considers the regional characteristics of tool positioning. This work extends the rolling ball method to 31/21/2-axis machining, thereby successfully delivering 5-axis quality with currently installed 3-axis computer numerical control milling machines. The pseudo-radius of curvature provides a novel geometrical subdivision criterion. Two Bezier curved surfaces are tested and compared with the 5-axis rolling ball method. Two additional surfaces are presented to further demonstrate the partitioning capability of the method. The results suggest that the rolling ball method for 31/21/2-axis machining is comparatively competitive in performance and quality.

关键词： Computer assisted manufacturing manufacturing technology computer numerical control machining 5-axis machining tool positioning surface partitioning path planning 31 2-axis machining pre-processing method algorithm milling rolling ball radius of curvature patch boundary modeling

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Essential processing methods of hyperspectral images of agricultural and food products

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2020年第0期198卷 103936-000页

作者： Jia, Beibei Wang, Wei Ni, Xinzhi Lawrence, Kurt C. Zhuang, Hong Yoon, Seung-Chul Gao, Zhixian China Agr Univ Coll Engn 17 Tsinghua East Rd Beijing 100083 Peoples R China USDA ARS Crop Genet & Breeding Res Unit 2747 Davis Rd Tifton GA 31793 USA USDA ARS Qual & Safety Assessment Res Unit Athens GA 30605 USA Tianjin Inst Hlth & Environm Med Tianjin Key Lab Risk Assessment & Control Technol Tianjin 300050 Peoples R China

Hyperspectral images integrate spatial and spectral details together. They can provide valuable information about both external physical and internal chemical characteristics of agricultural and food products rapidly and non-destructively. Despite rapid improvements in instruments and acquisition techniques, the collected high-quality hyperspectral images still contain much useless information, like uneven illumination, background, specular reflection, and bad pixels that need to be removed. That is, hyperspectral image preprocessing is necessary for almost each hyperspectral image to get pure images or pixels, or to reduce negative influences on the subsequent detection, classification, and prediction analysis. This manuscript will enumerate some possible solutions to deal with issues mentioned above before further image analyzing. The advantages and disadvantages of different methods when dealing with a specific problem are also discussed. Obtained clean images or pure signals can be used for further data analysis. Finally, post-processing of hyperspectral images can be carried out to enhance the classification result of images or to generate chemical images/distribution maps to show spatial component concentration distributions of non-homogeneous samples.

关键词： Hyperspectral image pre-processing method Uneven illumination Post-processing method Distribution maps

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Switched projected gradient descent algorithms for secure state estimation under sparse sensor attacks

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AUTOMATICA 2019年 103卷 503-514页

作者： Lu, An-Yang Yang, Guang-Hong Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China

This paper investigates the secure state estimation problem of cyber-physical systems (CPSs) under sparse sensor attacks. First, a novel algorithm, which uses a switched gradient descent technique to harness the intrinsic combinatorial complexity of the secure state estimation problem, is proposed to estimate the state. The computational complexity is reduced through improving the convergence rate, reducing the number of candidates to be searched, reducing the search times, and reducing the computing resources consumed by each incorrect candidate selection simultaneously. Second, based on the proposed switched gradient descent algorithm, an observer-based algorithm is proposed to efficiently update the state estimation while new measurements are available. Compared with the existing methods, the computational complexity is reduced greatly without introducing any constraint except the basic observability assumption by adopting the proposed algorithms. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Cyber-physical systems Secure state estimation Switched gradient descent algorithm Luenberger observer pre-processing method

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High sidelobe analysis and reduction in multistatic inverse synthetic aperture radar imaging fusion with gapped data

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IET RADAR SONAR AND NAVIGATION 2019年第7期13卷 1200-1206页

作者： Kang, Hailong Li, Jun Li, Han Zhang, Yuhong Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China Xidian Univ Sch Elect Engn Xian 710071 Shaanxi Peoples R China

Radar observations from different angles are often discontinuous in multistatic inverse synthetic aperture radar (ISAR) imaging. Based on Fourier transform, such as Polar Format Algorithm and Range Doppler Algorithm, the discontinuity of the angle will make the performance of traditional ISAR imaging algorithm worse. The sidelobe of the image will rise and the mainlobe may split. Generally, it is necessary to pre-process the gapped data and then the traditional ISAR imaging algorithm is used for imaging. The most commonly used pre-processing method is to interpolate the gap. However, the performance of this method is not satisfied, especially when the gap is large. The reason of sidelobe rising and mainlobe splitting is first analysed. Then, a sidelobe reduction method based on compressive sensing (CS) is proposed. This method establishes a relationship between the complete data and the gapped data, and the complete data can be solved from the gapped data by CS method. After that, the complete data will be used for imaging by utilising traditional ISAR imaging algorithm and the high sidelobe will be reduced effectively. The effectiveness of the proposed method is verified by the analysis and the simulation results.

关键词： synthetic aperture radar Fourier transforms radar imaging image fusion high sidelobe analysis multistatic inverse synthetic aperture radar imaging gapped data radar observations Polar Format Algorithm Range Doppler Algorithm traditional ISAR imaging algorithm pre-processing method sidelobe rising sidelobe reduction method complete data

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Visible and near-infrared reflectance spectroscopy-An alternative for monitoring soil contamination by heavy metals

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JOURNAL OF HAZARDOUS MATERIALS 2014年 265卷 166-176页

作者： Shi, Tiezhu Chen, Yiyun Liu, Yaolin Wu, Guofeng Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Peoples R China Wuhan Univ Minist Educ Key Lab Geog Informat Syst Wuhan 430079 Peoples R China Shenzhen Univ Natl Adm Surveying Mapping & Geoinformat Key Lab Geoenvironm Monitoring Coastal Zone Shenzhen 518060 Peoples R China Shenzhen Univ Shenzhen Key Lab Spatial Smart Sensing & Serv Shenzhen 518060 Peoples R China Shenzhen Univ Coll Life Sci Shenzhen 518060 Peoples R China

Soil contamination by heavy metals is an increasingly important problem worldwide. Quick and reliable access to heavy metal concentration data is crucial for soil monitoring and remediation. Visible and near-infrared reflectance spectroscopy, which is known as a noninvasive, cost-effective, and environmentally friendly technique, has potential for the simultaneous estimation of the various heavy metal concentrations in soil. Moreover, it provides a valid alternative method for the estimation of heavy metal concentrations over large areas and long periods of time. This paper reviews the state of the art and presents the mechanisms, data, and methods for the estimation of heavy metal concentrations by the use of visible and near-infrared reflectance spectroscopy. The challenges facing the application of hyperspectral images in mapping soil contamination over large areas are also discussed. (C) 2014 Elsevier B.V. All rights reserved.

关键词： pre-processing method Spectral index Variable selection method Modeling strategy Calibration method Hyperspectral image

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Spectrometric Classification of Bamboo Shoot Species by Comparison of Different Machine Learning methods

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FOOD ANALYTICAL methodS 2021年第2期14卷 300-306页

作者： Tong, Long Li, Bin Geng, Yanhui Chen, Lijie Li, Yanjie Cao, Ruishu Chongqing Acad Forestry Chongqing 400036 Peoples R China Chinese Acad Forestry Res Inst Subtrop Forestry Hangzhou 311400 Zhejiang Peoples R China Massey Univ Inst Hort Sci Private Bag 11222 Palmerston North 4442 New Zealand

The nutrition and quality of bamboo shoots from different species have a large variation, and traditional methods used for the classification of different bamboo shoot species are expensive and time-consuming. Here, the capability of near-infrared reflectance (NIR) spectroscopy to identify bamboo shoot species in a time- and cost-effective manner was examined. The NIR spectra of four bamboo shoot species were collected. Three classification models, a support vector machine (SVM), partial least squares-discriminant analysis (PLSDA), and random forest (RF), were calibrated. Several spectra pre-processing methods and their combination were trained before model calibration for the best classification model collection;each model was run 200 times for the calculation of the prediction error and model stability checking. The SVM model combined with the Det+2nd derivative had the best performance with an overall accuracy of 0.95. The use of less than 16% of the full-length NIR spectra produced a similar high accuracy of 0.91. Eight important regions, 1015, 1135, 1175, 1338, 1380, 1620, 1690, and 1750 nm, were found to be highly related to the classification of bamboo shoots. This study found that NIR spectra combined with SVM methods produced a rapid and non-destructive approach for the classification of bamboo shoot species.

关键词： NIR spectroscopy Model Bamboo shoot pre-processing method Variable selection

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