- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Features of Wavelet Analysis in X-Ray Reflectometry of Thin Films
摘要： Specific features of the use of wavelet transform for estimating the thickness of layers and their order in a film density profile based on X-ray and synchrotron reflectometry data are considered. Some ways are proposed to reveal the characteristic features of Langmuir film packing by constructing a wavelet transform for the corresponding reflectograms. Dependences of the X-ray attenuation length on the grazing incidence angle are plotted by an example of multilayered box model of film profile; these dependences demonstrate possibilities of mapping the spatial signal delay (which occurs when rays are reflected from layers of different density) in a waveletgram.
关键词： wavelet transform,thin films,attenuation length,Langmuir film packing,X-ray reflectometry
更新于2025-09-23 15:21:01
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[IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Voice Pathology Detection Based on the Vocal Fold Signal and the Vocal Tract Signal Separation
摘要： Voice pathology correlates with vocal fold problems, so extracting valid features from the vocal fold excitation signal is helpful for classifying the normal and pathological voice. A novel feature extraction method which combines wavelet packet decomposition and nonlinear feature extraction is proposed in this paper. The original speech signals are firstly decomposed into 5 layers using wavelet packet-based method, and the high frequency signals which correlate with the vocal fold are reconstructed. Then nonlinear features are extracted from the reconstructed signals. Support Vector Machine is used to classify the normal and pathological voice using the nonlinear features. The proposed method and features are evaluated on the Massachusetts Eye and Ear Infirmary databases. The second-order renyi entropy features give very promising classification accuracy of 98.21%. The highest accuracy is 99.21% when the Hurst parameter and second-order renyi entropy features are combined. Experimental results show that the vocal fold excitation signal can express the pathological information about sound efficiently, which can be used for the automatic detection and classification of the pathological voice.
关键词： support vector machine,wavelet packet,entropy,vocal fold excitation
更新于2025-09-23 15:21:01
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Joint Image Compression and Encryption Using IWT with SPIHT, Kd-Tree and Chaotic Maps
摘要： Confidentiality and efficient bandwidth utilization require a combination of compression and encryption of digital images. In this paper, a new method for joint image compression and encryption based on set partitioning in hierarchical trees (SPIHT) with optimized Kd-tree and multiple chaotic maps was proposed. First, the lossless compression and encryption of the original images were performed based on integer wavelet transform (IWT) with SPIHT. Wavelet coefficients undergo diffusions and permutations before encoded through SPIHT. Second, maximum confusion, diffusion and compression of the SPIHT output were performed via the modified Kd-tree, wavelet tree and Huffman coding. Finally, the compressed output was further encrypted with varying parameter logistic maps and modified quadratic chaotic maps. The performance of the proposed technique was evaluated through compression ratio (CR) and peak-signal-to-noise ratio (PSNR), key space and histogram analyses. Moreover, this scheme passes several security tests, such as sensitivity, entropy and differential analysis tests. According to the theoretical analysis and experimental results, the proposed method is more secure and decreases the redundant information of the image more than the existing techniques for hybrid compression and encryption.
关键词： k-dimensional tree,chaotic maps,set partition in hierarchical trees,integer wavelet transform,encryption,image compression
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) - Bangalore, India (2019.11.15-2019.11.16)] 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) - Closed-Loop Control of a DC-DC Four-Phase Interleaved Quadrupler for Solar Photovoltaic Applications
摘要： We propose ?lter banks in the graph spectral domain, where each ?lter is de?ned by a sum of sinusoidal waves. The main advantages of these ?lter banks are that (a) they have low approximation errors even if a lower-order shifted Chebyshev polynomial approximation is used, (b) the upper bound of the error after the pth order Chebyshev polynomial approximation can be calculated rigorously without complex calculations, and (c) their parameters can be ef?ciently obtained from any real-valued linear phase ?nite impulse response ?lter banks in regular signal processing. The proposed ?lter bank has the same ?lter characteristics as the corresponding classical ?lter bank in the frequency domain and inherits the original properties, such as tight frame and no DC leakage. Furthermore, their approximation orders can be determined from the desired approximation accuracy. The effectiveness of our approach is evaluated by comparing them with existing spectral graph wavelets and ?lter banks.
关键词： spectral graph wavelet,spectral graph ?lter bank,Graph signal processing,Chebyshev polynomial approximation
更新于2025-09-23 15:19:57
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A hybrid random forest method fusing wavelet transform and variable importance for quantitative analysis of K in potassic salt ore using laser-induced breakdown spectroscopy
摘要： Potash mine is the main raw material for the production of agricultural fertilizers. In this research, random forest(RF) models fusing variable importance and wavelet transform were proposed to determine the K content in potassic salt ore. 53 potassic salts samples were analyzed, 37 of which were treated as calibration set. An original RF model was developed for the regression with optimized parameters ntree and mtry. The R2P (0.7399) and the modeling time (251.8s) of RF model were not satisfied. We first explored the effect of different variable importance(VI) thresholds on quantitative results. As the VI threshold was set to 0.090, the variable number of VIRF model was reduced from 27620 to 3355. There were no significant improvements for VIRF in other model performance parameters like RMSEP and R2P. Then wavelet transform was adopted to screen the input variables of the RF model (defined as WTRF). Their promotion ratios are 16% (R2P from 0.7399 to 0.8555), 38% (RMSEP from 0.1798 to 0.1106) and 62% (MRE from 0.2740 to 0.1032), 11% (MRSD from 0.0686 to 0.0613), respectively. As for modeling time, it was promoted by about three orders of magnitude. When using the variable importance for the WTRF model further (defined as WT-VIRF), because all the selected input variables filtering by wavelet transform contributed a lot to the quantitative results, therefore no more variable were got rid of, and then WT-VIRF model got the exact same result with WTRF model. All the results demonstrated shows that the RF model combining WT is a promising methodology for quantitative analysis of K content in potassic salt ore.
关键词： Wavelet Transform,Potash,LIBS,Variable Importance
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Alignment Tolerance Control of the Micro CPV Array Using Monte Carlo Methods
摘要： Forest degradation is an important issue in global environmental studies, albeit not yet well defined in quantitative terms. The present work addresses the problem, by starting with the assumption that forest spatial structure can provide an indication of the process of forest degradation, this being reflected in the spatial statistics of synthetic aperture radar (SAR) backscatter observations. The capability of characterizing landcover classes, such as intact and degraded forest (DF), is tested by supervised analysis of ENVISAT ASAR and ALOS PALSAR backscatter spatial statistics, provided by wavelet frames. The test is conducted in a closed semideciduous forest in Cameroon, Central Africa. Results showed that wavelet variance scaling signatures, which are measures of the SAR backscatter two-point statistics in the combined space-scale domain, are able to differentiate landcover classes by capturing their spatial distribution. Discrimination between intact and DF was found to be enabled by functional analysis of the wavelet scaling signatures of C-band ENVISAT ASAR data. Analytic parameters, describing the functional form of the scaling signatures when fitted by a third-degree polynomial, resulted in a statistically significant difference between the signatures of intact and DF. The results with ALOS PALSAR, on the other hand, were not significant. The technique sets the stage for promising developments for tracking forest disturbance, especially with the future availability of C-band data provided by ESA Sentinel-1.
关键词： texture,wavelet transform,synthetic aperture radar (SAR),spatial statistics,Degraded forest (DF)
更新于2025-09-23 15:19:57
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The Antibody-Free Recognition of Cancer Cells Using Plasmonic Biosensor Platforms with the Anisotropic Resonant Metasurfaces
摘要： It is vital and promising for portable and disposable biosensing devices to achieve on-site detection and analysis of cancer cells. Although traditional labelling techniques provide an accurate quantitative measurement, the complicated cell staining and high-cost measurements limit its further development. Here, we demonstrate a non-immune biosensing technology. The plasmonic biosensors which is based on anisotropic resonant split ring resonators in terahertz range successfully realize the antibody-free recognition of cancer cells. The dependences of Δf and fitted phase slope (FPS) on the cancer cell concentration at different polarizations give new perspective in hexagonal radar maps. The results indicate that the lung cancer cell A549 and liver cancer cell HepG2 can be distinguished and determined simply based on the enclosed shapes in the radar maps without any antibody introduction. The minimum concentration of identification reduces as low as 1×104 cells/ml and such identification can be kept valid in a large range of cell concentration, ranging from 104 to 105. The construction of two-dimensional extinction intensity cards of corresponding cancer cells based on the wavelet transform method also supplies corresponding information for the antibody-free recognition and determination of two cancer cells. Our plasmonic MBs show a great potential in the determination and recognition of label-free cancer cells, being an alternative to non-immune biosensing technology.
关键词： terahertz,antibody-free biosensing,cancer cells,metasurfaces,continuous wavelet transform
更新于2025-09-23 15:19:57
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[Institution of Engineering and Technology 8th Renewable Power Generation Conference (RPG 2019) - Shanghai, China (24-25 Oct. 2019)] 8th Renewable Power Generation Conference (RPG 2019) - Arc Fault Detection and Localization in Photovoltaic Systems Based on Arc Signatures in Low Impedance Paths and Its Path Topology
摘要： Near-infrared spectroscopy (NIRS) has been proposed as a suitable technique for the analysis of cerebral autoregulation as it provides a simpler acquisition methodology and more artifact-free signal. A number of sophisticated wavelet transform methods have recently emerged to quantify the cerebral autoregulation mechanism using NIRS and blood pressure signals. These provide an enhanced partitioning of signal information via the time–frequency plane, which facilitates improved extraction of the components of interest. This area is reviewed, and enhancements to this form of analysis are suggested.
关键词： wavelet transform,Cerebral autoregulation,NIRS
更新于2025-09-23 15:19:57
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[IEEE 2019 International Conference on Power Electronics, Control and Automation (ICPECA) - New Delhi, India (2019.11.16-2019.11.17)] 2019 International Conference on Power Electronics, Control and Automation (ICPECA) - Fault Identification Algorithm for Grid Connected Photovoltaic Systems using Machine Learning Techniques
摘要： The motivation and background behind the fault detection for grid connected solar power plant is presented in this paper. The major issues encountered when integrating a PV system to the grid include multi-peak phenomenon due to partial shading, regulation of circulating currents, the impact of grid impedances on PV system stability, Fault Ride-Through (FRT) Capability, and anti-islanding detection. Hence, fault detection and condition monitoring system are necessary for smooth operation. In this paper, a fault classification technique for single-phase grid connected PV systems is developed. Wavelet Transform and Neural network approaches are used for developing the fault classification algorithm. The results depicted that the developed fault detection algorithm shows a significant improvement in the classification accuracy with 98.4%.
关键词： Wavelet Transform,fault classification,fault diagnosis,Neural Network,Photovoltaic System
更新于2025-09-23 15:19:57
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Combining Faraday Tomography and Wavelet Analysis
摘要： We present a concept for using long-wavelength broadband radio continuum observations of spiral galaxies to isolate magnetic structures that were only previously accessible from short-wavelength observations. The approach is based on combining the RM Synthesis technique with the 2D continuous wavelet transform. Wavelet analysis helps to isolate and recognize small-scale structures which are produced by Faraday dispersion. We ?nd that these structures can trace galactic magnetic arms as illustrated by the case of the galaxy NGC 6946 observed at λ = 17–22 cm. We support this interpretation through the analysis of a synthetic observation obtained using a realistic model of a galactic magnetic ?eld.
关键词： wavelet analysis,RM-synthesis,faraday depolarization,galactic magnetic field
更新于2025-09-19 17:15:36