wavelet

摘要： This work concerns the 10? North, 20? North African band. Area renowned for having some of the poorest countries in the world. It is also home to the Sahelian strip and part of the Sahara. The countries in this zone have a relatively low electrification rate compared to the enlightened country. To solve this problem, these countries want to turn to renewable energies such as photovoltaics (renewable energy obtained through solar radiation). Therefore, understanding the behavior of irradiation and cloudiness in the 10 - 20 band becomes necessary. The application of the empirical orthogonal functions to the different cloud layers and to the irradiation reveals a seasonality of the latter, in particular compared to the first modes of the empirical orthogonal functions (EOF1). Indeed, by filtering in time and space to isolate solar radiation and cloudiness, the EOF1 expresses respectively 94.3% of the variation of descending solar radiation in clear sky in the 10 - 20 band. Note 65.7% for global radiation, 54.4% for cloudiness at 450 hPa, 69.6% for cloudiness between 800 hPa and 450 hPa, 76.6% for low cloudiness, 61.4% for total cloudiness. These results allow us to say that we have generally good sunshine over several months, with little cloud cover in this band. However, since this zone is considered to be part of the main aerosol emission source zones, it is important in their temporal consideration of the optical depth. By doing the wavelet analysis on the optical depth data from Dakar and Banizoumbou, we note that the average dust presence spectrum over the entire period from 1997 to 2019 in the two stations with a slight shift compared to the peaks and the maximum observed value. A sign that there is a strong presence of dust in this area and that it should be taken into account for any photovoltaic installation in this area.

摘要： In this work,a tapered fluidized bed(TFB)without a distributor for fluidizing carbon nanotube(CNT)was applied for improving the dead zone,blockage,and fracture of distributor,which occurred in actual production.Experiments were performed under different superficial gas velocities,static bed heights,CNT agglomerate size,and positions of pressure probe.To obtain multi-perspective and multi-scale understanding of fluidization dynamics of gas–CNT flow in the TFB without a distributor,the standard deviation,skewness,kurtosis,wavelet decompositions and homogeneous index analysis methods were adopted.Some noticeable phenomena were observed.Particle movements including inter-particle,gas–particle and particle–wall dominate dynamic characteristics.The amplitudes of pressure fluctuations of coarse agglomerated multi-walled CNT were more sensitive to the gas velocity than that of fine agglomerated multi-walled CNT.The sensitively of energy contribution of the meso-and macrostructures was that the sensitivity of the measured position was less than the sensitivity of the energy contribution by the changes of particle size,and the sensitivity of the energy contribution by the changes of particle size was less than the energy contribution by the changes of gas velocity.The fluidization quality of coarse agglomerated multi-walled CNT was better than that of fine agglomerated multi-walled CNT,which was verified by the skewness and wavelet analysis.

摘要： We investigated the relationship between solar activity, total ozone, and solar ultraviolet B (UV-B) radiation from the perspective of multi-fractality. Fractal properties are observed in the time series of the dynamics of complex systems. To detect the changes in fractality, we performed a multifractal analysis using a wavelet transform. The changes in fractality indicated that solar activity was closely related to the total ozone and that the total ozone had a strong effect on UV-B radiation. For high solar activity, the F10.7 flux and global total ozone exhibited monofractality. The F10.7 flux and total ozone also increased, and a change from multifractality to monofractality was observed. This corresponded to the formation of the order. The strong interactions between the solar flux and ozone occur during the high solar activity. In contrast, UV-B radiation increased and showed multifractality, when fluctuations in UV-B radiation became large. For low solar activity, the F10.7 flux and total ozone exhibited multifractality, and UV-B radiation exhibited monofractality. Hence, the change in fractality of the F10.7 flux and total ozone was the opposite of UV-B radiation. A significant change in fractality for F10.7 flux and SSN, which had a significant fluctuation and a slight change in fractality for UV-B radiation, and total ozone were identified.

摘要： In this paper,we analyze the time-series graphs of Bitcoin price and Twitter-based economic uncertainty index over the past two years and use a wavelet coherence graph to determine their relationship.We found a causal relationship between Bitcoin(BTC)and Twitter-based economic uncertainty(TEU)index in different frequency bands,which would help predict Bitcoin price movements in the future.Our study provides reference to academics and investors.

摘要： 针对CT图像在生成或传输时容易受到噪声影响这一难题,提出了基于Contourlet变换结合PCA阈值的去噪方法.首先,对噪声图像进行Contourlet变换.然后,对DFB方向滤波后得到的Contourlet系数进行PCA阈值及硬阈值函数去噪.最后,对去噪后的Contourlet系数进行Contourlet逆变换,得到去噪图像.通过对图像添加噪声并与Contourlet结合六种不同阈值去噪方法进行对比,采用PSNR评估去噪优劣.结果 表明:贝叶斯阈值方法PSNR值最高PSNR=94.88 dB,然后是PCA阈值PSNR=83.02 dB,最后依次是配套改进阈值PSNR=73.97 dB、3σ阈值PSNR=73.27 dB、统一阈值PSNR=72.33 dB、通用阈值PSNR=71.50 dB.PCA阈值去噪结果整体平滑性较好,视觉效果较好;贝叶斯阈值去噪结果整体平滑性较差,视觉效果不佳.通过将Contourlet变换框架取代传统小波变换框架并结合PCA阈值应用在图像去噪中,不仅信噪比有所提高,而且图像视觉效果也明显改善.

摘要： Structural health monitoring(SHM)is a process of implementing a damage detection strategy in existing structures to evaluate their condition to ensure safety.The changes in the material,geometric and/or structural properties affect structural responses,which can be captured and analyzed for condition assessment.Various vibration-based damage detection algorithms have been developed in the past few decades.Among them,wavelet transform(WT)gained popularity as an efficient method of signal processing to build a framework to identify modal properties and detect damage in structures.This article presents the state-of-the-art implementation of various WT tools in SHM with a focus on civil structures.The unique features and limitations of WT,and a comparison of WT and other signal processing methods,are further discussed.The comprehensive literature review in this study will help interested researchers to investigate the use of WT in SHM to meet their specific needs.

摘要： Assume that(X,d,μ) is a space of homogeneous type in the sense of Coifman and Weiss(1971,1977). In this article, motivated by the breakthrough work of Auscher and Hyt(o¨)nen(2013) on orthonormal bases of regular wavelets on spaces of homogeneous type, we introduce a new kind of approximations of the identity with exponential decay(for short, exp-ATI). Via such an exp-ATI, motivated by another creative idea of Han et al.(2018) to merge the aforementioned orthonormal bases of regular wavelets into the frame of the existed distributional theory on spaces of homogeneous type, we establish the homogeneous continuous/discrete Calderón reproducing formulae on(X, d,μ), as well as their inhomogeneous counterparts. The novelty of this article exists in that d is only assumed to be a quasi-metric and the underlying measure μ a doubling measure,not necessary to satisfy the reverse doubling condition. It is well known that Calderón reproducing formulae are the cornerstone to develop analysis and, especially, harmonic analysis on spaces of homogeneous type.

摘要： Ground Penetration Radar is a controlled source geophysical method which uses high frequency electromagnetic waves to study shallow layers. Resolution of this method depends on difference of electrical properties between target and surrounding electrical medium, target geometry and used bandwidth. The wavelet transform is used extensively in signal analysis and noise attenuation. In addition, wavelet domain allows local precise descriptions of signal behavior. The Fourier coefficient represents a component for all time and therefore local events must be described by the phase characteristic which can be abolished or strengthened over a large period of time. Finally basis of Auto Regression (AR) is the fitting of an appropriate model on data, which in practice results in more information from data process. Estimation of the parameters of the regression model (AR) is very important. In order to obtain a higher-resolution spectral estimation than other models, recursive operator is a suitable tool. Generally, it is much easier to work with an Auto Regression model. Results shows that the TQWT in soft thresholding mode can attenuate random noise far better than TQWT in hard thresholding mode and Autoregressive-FX method.

摘要： The brain is a unique organization in nature, possessing the ability for psychic activity, which manifests itself in thoughts, feelings and emotions. In present days, numbers of mathematical methods for analysis of electroencephalogram (EEG) were developed with continuous wavelet transform being one of the most successive approaches for studying of brain activity. This paper is aimed to develop methods for investigation of psychic brain activity with help of continuous wavelet analysis of EEG. Ability of human to realize semantic content of the image presented on the screen was tested. Experiment was accompanied with simultaneous EEG recording, which was held with developed software and PC-based experimental setup. The information capabilities of continuous wavelet transform-based method for EEG analysis were improved for the recognition of specific patterns in human brain activity. Comparative wavelet analysis was carried out for EEG recordings at the moment of awareness of the semantic content of the image and for EEG recordings in the absence of conscious (subjective) perception of the semantic content of the image. Significant differences were shown in the alpha rhythm of EEG for the moments of awareness of the semantic content of the image and for the moments of absence of conscious perception. Continuous wavelet analysis of EEG showed that the alpha rhythm is the main EEG rhythm, which can be used to estimate the presence of subjective perception of the visual image. Significant differences were shown in the alpha rhythm of EEG for the moments of awareness of the semantic content of the image and for the moments of absence of conscious perception. Conducted studies allow to conclude that revealing of brain activity related to visual image awareness is possible through analysis of EEG.

摘要： With the continuous development of technology, face recognition technology has played an important role in police work. In order to get a clear face image, image preprocessing technology is needed. This paper mainly proposes illumination compensation technology and reconstruction technology based on symmetry.

摘要： Errors of mismatch and currents calibration caused by channel geometrical variety in switched-current are investigated in this paper. The relation and computing of mismatch and sensitivity are discussed also, and then a measure method of switched current mismatch using wavelet decomposition is proposed. A selected group of same transconductance is choosing as a cohort firstly, and the sensitivities of cohort in relation to the variation of transconductance are computed. Compared with the nominal deviation and tolerance borderline, the optimization and testing can be performed. As an example, a sixth order chebyshev low-pass filter is simulated and tested. The results have justified the reliability and feasibility of the method.

摘要： 牛奶消费需求预测对牛奶价格的稳定以及牛奶业生产的计划安排、销售决策具有重要意义。本文选取牛奶的全国年度消费量作为研究对象，提出基于经验模态分解（Ensemble Empirical Mode， EMD）/小波（Wavelet）分解和最小二乘支持向量回归（Least Squares Support Vector Regression ，LSSVR）的分解集成方法，以对牛奶消费需求量进行预测研究。实证检验表明，本文所提出的分解集成预测方法相比单一预测模型能更为有效的预测牛奶消费需求。预测结果表明，我国牛奶消费需求2009年相比上年有所下降，2010年呈上升趋势，而2011年又将有明显的下降。这将有助于有关决策部门提前做好调控工作，从而保证奶业市场的健康发展。

摘要： 牛奶消费需求预测对牛奶价格的稳定以及牛奶业生产的计划安排、销售决策具有重要意义。本文选取牛奶的全国年度消费量作为研究对象，提出基于经验模态分解（Ensemble Empirical Mode， EMD）/小波（Wavelet）分解和最小二乘支持向量回归（Least Squares Support Vector Regression ，LSSVR）的分解集成方法，以对牛奶消费需求量进行预测研究。实证检验表明，本文所提出的分解集成预测方法相比单一预测模型能更为有效的预测牛奶消费需求。预测结果表明，我国牛奶消费需求2009年相比上年有所下降，2010年呈上升趋势，而2011年又将有明显的下降。这将有助于有关决策部门提前做好调控工作，从而保证奶业市场的健康发展。

摘要： 牛奶消费需求预测对牛奶价格的稳定以及牛奶业生产的计划安排、销售决策具有重要意义。本文选取牛奶的全国年度消费量作为研究对象，提出基于经验模态分解（Ensemble Empirical Mode， EMD）/小波（Wavelet）分解和最小二乘支持向量回归（Least Squares Support Vector Regression ，LSSVR）的分解集成方法，以对牛奶消费需求量进行预测研究。实证检验表明，本文所提出的分解集成预测方法相比单一预测模型能更为有效的预测牛奶消费需求。预测结果表明，我国牛奶消费需求2009年相比上年有所下降，2010年呈上升趋势，而2011年又将有明显的下降。这将有助于有关决策部门提前做好调控工作，从而保证奶业市场的健康发展。

摘要： 牛奶消费需求预测对牛奶价格的稳定以及牛奶业生产的计划安排、销售决策具有重要意义。本文选取牛奶的全国年度消费量作为研究对象，提出基于经验模态分解（Ensemble Empirical Mode， EMD）/小波（Wavelet）分解和最小二乘支持向量回归（Least Squares Support Vector Regression ，LSSVR）的分解集成方法，以对牛奶消费需求量进行预测研究。实证检验表明，本文所提出的分解集成预测方法相比单一预测模型能更为有效的预测牛奶消费需求。预测结果表明，我国牛奶消费需求2009年相比上年有所下降，2010年呈上升趋势，而2011年又将有明显的下降。这将有助于有关决策部门提前做好调控工作，从而保证奶业市场的健康发展。

摘要： 牛奶消费需求预测对牛奶价格的稳定以及牛奶业生产的计划安排、销售决策具有重要意义。本文选取牛奶的全国年度消费量作为研究对象，提出基于经验模态分解（Ensemble Empirical Mode， EMD）/小波（Wavelet）分解和最小二乘支持向量回归（Least Squares Support Vector Regression ，LSSVR）的分解集成方法，以对牛奶消费需求量进行预测研究。实证检验表明，本文所提出的分解集成预测方法相比单一预测模型能更为有效的预测牛奶消费需求。预测结果表明，我国牛奶消费需求2009年相比上年有所下降，2010年呈上升趋势，而2011年又将有明显的下降。这将有助于有关决策部门提前做好调控工作，从而保证奶业市场的健康发展。

摘要： 目前,无线传感器网络在智能环境检测,灾难控制,战场侦察,安全监视方面取得了日益广泛的应用,引起人们日益关注,亟须仿真平台来研究无线传感器网络,在分析无线传感器网络能量消耗特征的基础上,利用小波变换生成一步转移矩阵,基于Markov模型提出了无线传感器网络节点能量消耗模型。仿真结果表明,与真实的无线传感器网络节点相比,能够有效地描述出无线传感器网络节点能量消耗过程。

摘要： 目前,无线传感器网络在智能环境检测,灾难控制,战场侦察,安全监视方面取得了日益广泛的应用,引起人们日益关注,亟须仿真平台来研究无线传感器网络,在分析无线传感器网络能量消耗特征的基础上,利用小波变换生成一步转移矩阵,基于Markov模型提出了无线传感器网络节点能量消耗模型。仿真结果表明,与真实的无线传感器网络节点相比,能够有效地描述出无线传感器网络节点能量消耗过程。

摘要： 目前,无线传感器网络在智能环境检测,灾难控制,战场侦察,安全监视方面取得了日益广泛的应用,引起人们日益关注,亟须仿真平台来研究无线传感器网络,在分析无线传感器网络能量消耗特征的基础上,利用小波变换生成一步转移矩阵,基于Markov模型提出了无线传感器网络节点能量消耗模型。仿真结果表明,与真实的无线传感器网络节点相比,能够有效地描述出无线传感器网络节点能量消耗过程。

摘要： 目前,无线传感器网络在智能环境检测,灾难控制,战场侦察,安全监视方面取得了日益广泛的应用,引起人们日益关注,亟须仿真平台来研究无线传感器网络,在分析无线传感器网络能量消耗特征的基础上,利用小波变换生成一步转移矩阵,基于Markov模型提出了无线传感器网络节点能量消耗模型。仿真结果表明,与真实的无线传感器网络节点相比,能够有效地描述出无线传感器网络节点能量消耗过程。

摘要： 本发明公开了一种基于EMD‑Wavelet的MFCC相似度的语音段检测方法。采集说话人的语音信号作为源信号；利用经验模态分解(EMD)对含噪的语音信号进行分解，得到体现语音信号高低频能量的各阶本征模函数(IMF)；以各阶IMF分量的自相关系数的方差确定噪声为主导模态的IMF阶数，对噪声为主导模态的IMF进行小波阈值降噪，用降噪后的低阶IMF分量和余下的高阶IMF分量重构，获得降噪后的语音信号；计算语音信号的Mel倒谱参数(MFCC)，以欧氏距离作为语音信号MFCC相似度的测度；从相似度曲线中可以明显区分语音段和噪声段，从而实现语音段的提取。相比于传统的检测方法，本发明具有更好的鲁棒性和适应性，语音段检测的准确率更高，能够很好的应用于语音信号的语音段提取。

摘要： 本发明公开了一种基于Wavelet和Wedgelet变换HMT模型的图像分割方法，它涉及图像处理领域。主要解决传统分割方法边缘保持差的缺点。其过程为：提取待分割图像每类的训练图像块，对其多尺度分解小波系数及小波系数的多尺度Wedgelet逼近进行加权平均，根据加权系数估计模型参数Θ，求出待分割图像在各尺度上数据块对应的似然值和每个像素点的似然值，即后融合所需的似然值

摘要： 本发明公开了一种基于EMD‑Wavelet的MFCC相似度的语音段检测方法。采集说话人的语音信号作为源信号；利用经验模态分解(EMD)对含噪的语音信号进行分解，得到体现语音信号高低频能量的各阶本征模函数(IMF)；以各阶IMF分量的自相关系数的方差确定噪声为主导模态的IMF阶数，对噪声为主导模态的IMF进行小波阈值降噪，用降噪后的低阶IMF分量和余下的高阶IMF分量重构，获得降噪后的语音信号；计算语音信号的Mel倒谱参数(MFCC)，以欧氏距离作为语音信号MFCC相似度的测度；从相似度曲线中可以明显区分语音段和噪声段，从而实现语音段的提取。相比于传统的检测方法，本发明具有更好的鲁棒性和适应性，语音段检测的准确率更高，能够很好的应用于语音信号的语音段提取。

摘要： 本发明涉及计算机网络安全领域的网络数据分析，具体涉及针对海量网络数据包进行索引和查询分析的方法。该发明能够快速准确地从海量的网络数据包中检索出符合条件的数据包，它基于一种新型的数据结构Wavelet Tree，同时索引和查询的功能也是通过该数据结构来实现，查询功能的过程如图1所示。该发明需要较少的空间来存储建立的索引文件，且支持多种复杂的查询，对某一属性的准确查询、范围查询以及最值的查询等等。

摘要： 本发明提供一种用于电梯的Wavelet OFDM调制解调方法，包括获得HD‑PLC帧；HD‑PLC帧进入PAM调制器，根据预定的、或者从信道估计算法中获得的结果，进行PAM预调制；经过预调制的HD‑PLC帧进入IWDT编码器，进行小波压缩编码；对编码后的数据进行功率控制。在本发明中，充分利用电缆低频衰减低的特点，大大扩展了传输距离；发射机在高于10MHz的频带上不再有信号，从而降低了共模噪声产生和传输的可能性；接收机不再兼顾10MHz～28MHz的频带，可以将接收机差分滤波器设计得更加锐利，对带外噪声抑制更加有效。

摘要： 基于Wavelet和Curvelet变换的红外图像背景抑制方法，它涉及一种红外图像处理方法，以解决在红外图像处理领域内对背景干扰进行抑制的方法存在的在实现背景杂波抑制的同时也会抑制掉有用的目标信息的问题。对原始红外图像分别进行Wavelet变换分解和Curvelet变换分解；分别对Wavelet系数和Curvelet系数保留不同分辨率下的高频分解系数，将低频分解系数置零；分别通过保留的Wavelet系数和Curvelet系数对分解的原始红外图像进行图像重构；通过多分辨率分解框架，对步骤四所得到的Wavelet系数重构图像和Curvelet系数重构图像分别进行图像融合，得到最终的红外图像背景抑制结果。

摘要： 本发明公开了一种基于Wavelet和Wedgelet变换HMT模型的图像分割方法，它涉及图像处理领域。主要解决传统分割方法边缘保持差的缺点。其过程为：提取待分割图像每类的训练图像块，对其多尺度分解小波系数及小波系数的多尺度Wedgelet逼近进行加权平均，根据加权系数估计模型参数Θ，求出待分割图像在各尺度上数据块对应的似然值和每个像素点的似然值，即后融合所需的似然值likelihood