- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Partial Least Squares Identification of Multi Look-Up Table Digital Predistorters for Concurrent Dual-Band Envelope Tracking Power Amplifiers
摘要： This paper presents a technique to estimate the coefficients of a multiple-look-up table (LUT) digital predistortion (DPD) architecture based on the partial least-squares (PLS) regression method. The proposed 3-D distributed memory LUT architecture is suitable for efficient FPGA implementation and compensates for the distortion arising in concurrent dual-band envelope tracking power amplifiers. On the one hand, a new variant of the orthogonal matching pursuit algorithm is proposed to properly select only the best LUTs of the DPD function in the forward path, and thus reduce the number of required coefficients. On the other hand, the PLS regression method is proposed to address both the regularization problem of the coefficient estimation and, at the same time, reducing the number of coefficients to be estimated in the DPD feedback identification path. Moreover, by exploiting the orthogonality of the PLS transformed matrix, the computational complexity of the parameters’ identification can be significantly simplified. Experimental results will prove how it is possible to reduce the DPD complexity (i.e., the number of coefficients) in both the forward and feedback paths while meeting the targeted linearity levels.
关键词： principal component analysis (PCA),look-up tables (LUTs),power amplifier (PA),envelope tracking (ET),partial least squares (PLS),Digital predistortion (DPD)
更新于2025-09-09 09:28:46
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Label-free Identification of Trace Microcystin-LR with Surface-Enhanced Raman Scattering Spectra
摘要： The analysis of trace microcystin-LR (MC-LR) plays important roles in environmental fields, especially in monitoring domestic water quality and safety, since it has particularly harmful effect on wild and domestic animals as well as humans at low doses. Herein, we combine confocal Raman spectroscopy with SERS-AG substrate to characterize the “fingerprint” information of MC-LR directly. High sensitivity of SERS-AG substrates was verified by utilizing the probe molecule Rhodamine 6G. Mapping spectra demonstrated good reproducibility of MC-LR identification with label-free surface-enhanced Raman scattering (SERS) strategy. Differences between SERS spectra of MC-LR and R6G, microcystin-RR were evaluated by calculating their scores and loading weights with an unsupervised exploratory principal component analysis method. Then, relationship between Raman intensities and concentrations was preliminary analyzed with SERS spectra of MC-LR and the lowest concentration of MC-LR identification was 10-6 mg.L-1 while using SERS-AG substrate. Thereafter, 68.6% quantitative recovery of 10-3 mg.L-1 MC-LR in tap water samples was obtained by the proposed label-free SERS method. These results showed that confocal Raman spectroscopy with label-free surface-enhanced Raman scattering strategy can handle the identification of trace MC-LR for monitoring water quality and safety worldwide in future.
关键词： principal component analysis,microcystin-LR,surface-enhanced Raman scattering
更新于2025-09-09 09:28:46
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Direct nanocrystallite size investigation in microstrained mixed phase TiO2 nanoparticles by PCA of Raman spectra
摘要： Mixed phase anatase and rutile TiO2 nanoparticles (30-67 % R/A) have been synthesized by single step laser pyrolysis. Parallel studies by XRD and Raman spectroscopy suggested possible deforming microstress inside certain samples, due to boundary interactions between neighbouring nanocrystallites in nanoparticles, phase instabilities and/or O/C contents. Microstress in nanoparticles supports anatase phase stability in competition with rutile phase. Williamson-Hall plot was used to evaluate crystallite size and strain. A tensile global microstrain in anatase crystallites, was observed for elevated C content titania nanoparticles, together with compressive microstrain in crystallites within O deficient TiO2 nanoparticles. XPS and TEM characterization opens insights into the processes behind this type of behaviour. Principal Component Analysis of Raman spectra was applied for batch auto-characterization of mixed phase nanoparticles, with emphasis upon the method ability to simultaneously appreciate crystallite size for both anatase and rutile phase. The method focuses on covariational matrix of multiple samples Raman spectra. It provides results in good agreement with XRD calculated crystallite dimensions for unstrained titania, while for samples with microstrains it returns the size closer to the one predicted by Williamson-Hall plot.
关键词： Microstrain,Anatase,Principal Component Analysis (PCA),Raman Spectroscopy,Williamson-Hall,Rutile,TiO2 nanoparticles
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - GPU Acceleration of UAV Image Splicing Using Oriented Fast and Rotated Brief Combined with PCA
摘要： In this study, an accelerating method of oriented FAST and rotated BRIEF combined with principal component analysis (ORB/PCA) is proposed for splicing detection of unmanned aerial vehicle (UAV) images. Compared to traditional scale-invariant feature transform (SIFT) and speeded up robust features (SURF) methods, the proposed ORB/PCA can not only be faster but also produce more accurate. Moreover, in order for the proposed ORB to be effective for image stitching process in near real-time, the Compute Unified Device Architecture (CUDA) application programming interface of graphics processing unit (GPU) is cooperated to speed up the proposed method. Experimental results show that the proposed GPU based ORB/PCA framework is suitable for splicing detection of UAV images in Earth remote sensing. It can improve the image stitching process both in time and accuracy compared to conventional methods.
关键词： oriented FAST and rotated BRIEF (ORB),principal component analysis (PCA),unmanned aerial vehicle (UAV),graphics processing unit (GPU)
更新于2025-09-09 09:28:46
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[ASME ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems - San Francisco, California, USA (Monday 27 August 2018)] ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems - Assessment of Damage Progression in Automotive Electronics Assemblies Subjected to Temperature and Vibration
摘要： Electronics in automotive underhood environments is used for a number of safety critical functions. Reliable continued operation of electronic safety systems without catastrophic failure is important for safe operation of the vehicle. There is need for prognostication methods, which can be integrated, with on-board sensors for assessment of accrued damage and impending failure. In this paper, leadfree electronic assemblies consisting of daisy-chained parts have been subjected to high temperature vibration at 5g and 155°C. Spectrogram has been used to identify the emergence of new low frequency components with damage progression in electronic assemblies. Principal component analysis has been used to reduce the dimensionality of large data-sets and identify patterns without the loss of features that signify damage progression and impending failure. Variance of the principal components of the instantaneous frequency has been shown to exhibit an initial damage progression, increasing trend during the attaining a maximum value and decreasing prior to failure. The unique behavior of the instantaneous frequency over the period of vibration can be used as a health-monitoring feature for identifying the impending failures in automotive electronics. Further, damage progression has been studied using Empirical Mode Decomposition (EMD) technique in order to decompose the signals into Independent Mode Functions (IMF). The IMF’s were investigated based on their kurtosis values and a reconstructed strain signal was formulated with all IMF’s greater than a kurtosis value of three. PCA analysis on the reconstructed strain signal gave better patterns that can be used for prognostication of the life of the components.
关键词： high temperature vibration,prognostication,Empirical Mode Decomposition,spectrogram,kurtosis,automotive electronics,principal component analysis
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Deep Semi-Nonnegative Matrix Factorization Based Unsupervised Change Detection of Remote Sensing Images
摘要： In the paper, an unsupervised change detection method for remote sensing (RS) images based on deep semi-nonnegative matrix factorization (semi-NMF) is proposed. Firstly, the difference image is generated in different ways, depending on the types of input images. Then principal component analysis (PCA) is applied on the difference image to form the feature matrix X for improving the capability against various noise. In order to exploit more useful information from the resulting feature matrix, deep semi-NMF is introduced to factorize X into L+1 factors consisting of L nonrestricted matrices {Fl}Ll=1 and nonnegative cluster indicator matrix GL. Finally, the binary change mask (CM) is generated by assigning the pixels into changed and unchanged classes according to maximum criterion. The experimental results on two pairs of multitemporal RS images demonstrate the effectiveness of the proposed method.
关键词： remote sensing,principal component analysis,Unsupervised change detection,deep semi-nonnegative matrix factorization
更新于2025-09-09 09:28:46
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Perceptual hashing for SAR image segmentation
摘要： Image segmentation is an important step in the implementation of the interpretation of synthetic aperture radar (SAR) image due to speckle. This article proposes a SAR image segmentation method based on perceptual hashing. The new algorithm is divided into two phases. The first phase is to obtain initial regions with multi-thresholding based on histogram after reducing the speckle noise. The initial regions are used as input data. And the next phase is to merge regions according to the similarity between regions. In this phase, to segment SAR image effectively, the proposed hashing algorithm is used to obtain hash value and similarity between regions, which preserve the texture features of SAR images. In addition, we can obtain a smooth segmentation result by reducing the redundant information with principal component analysis. Furthermore, morphological methods are used to eliminate the uneven background in the segmentation results. These improvements make our algorithm more effective to segment the images with high speed. The experimental results of four real and one synthetic SAR images verify the efficiency of our algorithm.
关键词： multi-thresholding,perceptual hashing,region merging,principal component analysis,SAR image segmentation
更新于2025-09-09 09:28:46
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Fast reconstruction of hyperspectral radiative transfer simulations by using small spectral subsets: application to the oxygen A band
摘要： Hyperspectral radiative transfer simulations are a versatile tool in remote sensing but can pose a major computational burden. We describe a simple method to construct hyperspectral simulation results by using only a small spectral subsample of the simulated wavelength range, thus leading to major speedups in such simulations. This is achieved by computing principal components for a small number of representative hyperspectral spectra and then deriving a reconstruction matrix for a specific spectral subset of channels to compute the hyperspectral data. The method is applied and discussed in detail using the example of top-of-atmosphere radiances in the oxygen A band, leading to speedups in the range of one to two orders of magnitude when compared to radiative transfer simulations at full spectral resolution.
关键词： hyperspectral radiative transfer simulations,oxygen A band,principal component analysis,remote sensing,computational efficiency
更新于2025-09-09 09:28:46
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[Mathematics and Visualization] Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE, Bergen, Norway, August 29 – September 2, 2016) || Relaxed Optimisation for Tensor Principal Component Analysis and Applications to Recognition, Compression and Retrieval of Volumetric Shapes
摘要： The mathematical and computational backgrounds of pattern recognition are the geometries in Hilbert space used for functional analysis and the applied linear algebra used for numerical analysis, respectively. Organs, cells and microstructures in cells dealt with in biomedical image analysis are volumetric data. We are required to process and analyse these data as volumetric data without embedding into higher-dimensional vector spaces from the viewpoint of object-oriented data analysis. Therefore, sampled values of volumetric data are expressed as three-way array data. The aim of the paper is to develop relaxed closed forms for tensor principal component analysis (PCA) for the recognition, classification, compression and retrieval of volumetric data. Tensor PCA derives the tensor Karhunen-Loève transform, which compresses volumetric data, such as organs, cells in organs and microstructures in cells, preserving both the geometric and statistical properties of objects and spatial textures in the space.
关键词： pattern recognition,Karhunen-Loève transform,tensor principal component analysis,data compression,volumetric data
更新于2025-09-09 09:28:46
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Generation of enhanced information image using curvelet-transform-based image fusion for improving situation awareness of observer during surveillance
摘要： Image fusion has been widely used to combine multispectral information into an enhanced information image. The application of such enhanced information content in the field of surveillance for improving situation awareness of observer is highly recommended. When a single sensor information is used for surveillance like visible camera output during poor ambient lighting conditions, ‘hot-target’ details are not visible to the observer. The use of visible-infrared fused image is recommended during surveillance in poor ambient lighting conditions to visualise background scene details and ‘hot-target’ details simultaneously. A wrapping-based curvelet transform method is proposed for fusion of infrared and visible images. Curvelet transform is used because of its advantages over wavelet transform limitations like directional insensitivity, isotropic basis and inability to resolve curves. The approximation coefficients are fused using the principal component analysis rule while detailed coefficients are fused using absolute maximum rule. The reconstructed fused image is compared with results of other fusion approaches proposed in literature. The performance of proposed wrapping-based curvelet fusion method is found visually and statistically better in comparison to other fused image outputs. The fused image obtained using proposed method retains background details as well as hot target presence with fidelity.
关键词： Curvelet transform,infrared image,situation awareness,visible image,principal component analysis,image fusion
更新于2025-09-09 09:28:46