Wavelet Analysis

In this paper, a new computation method derived to solve the problems of approximation theory. This method is based upon pseudo-Chebyshev wavelet approximations. The pseudo-Chebyshev wavelet is being presented for the first time. The pseudo-Chebyshev wavelet is constructed by the pseudo-Chebyshev functions. The method is described and after that the error bounds of a function is analyzed. We have illustrated an example to demonstrate the accuracy and efficiency of the pseudo-Chebyshev wavelet approximation method and the main results. Four new error bounds of the function related to generalized Lipschitz class via the pseudo-Chebyshev wavelet are obtained. These estimators are the new fastest and best possible in theory of wavelet analysis. Key words and phrases: Lip [0,1) α class of functions, Lip [0,1) ξ class of functions, wavelet, multiresolution analysis, pseudo-Chebyshev function, pseudo-Chebyshev wavelet.

Atmospheric electric field (AEF) measurements were carried out in three different sites forming a triangular array in Southern Portugal. The campaign was performed during the summer characterized by Saharan dust outbreaks; the 16th-17th July 2014 desert dust event is considered here. Evidence of long-range dust electrification is attributed to the air-Earth electrical current creating a positive space-charge inside of the dust layer. An increase of ~23 V/m is observed in AEF on the day of the dust event corresponding to space-charges of ~20-2 pCm-3 (charge layer thicknesses ~10-100 m). A reduction of AEF is observed after the dust event.

An optimal lead is derived by linear transformation of the available primary lead signals, which maximizes certain criteria for distinction of an atypical beat from the typical ones. In this new ECG lead the atypical beats are enhanced and can be distinguished easily from the typical ones. A new fast algorithm for calculation of the optimal transformation is suggested which reduces substantially the number of transformation iterations. The method is compared to the original 'full combination set' method and similar results are obtained. This algorithm reduces drastically the calculation time and now standard 12-leads ECG preprocessing can be performed in reasonable time. Some preliminary results with standard 12-lead preprocesing are given.

Landcover change alters not only the surface landscape but also regional carbon and water cycling. The objective of this study was to assess the potential impacts of landcover change across the Kansas River Basin (KRB) by comparing local microclimatic impacts and regional scale climate influences. This was done using a 25-year time series of Normalized Difference Vegetation Index (NDVI) and precipitation (PPT) data analyzed using multi-resolution information theory metrics. Results showed both entropy of PPT and NDVI varied along a pronounced PPT gradient. The scalewise relative entropy of NDVI was the most informative at the annual scale, while for PPT the scalewise relative entropy varied temporally and by landcover type. The relative entropy of NDVI and PPT as a function of landcover showed the most information at the 512-day scale for all landcover types, implying different landcover types had the same response across the entire KRB. This implies that land use decisions may dramatically alter the local time scales of responses to global climate change. Additionally, altering land cover (e.g., for biofuel production) may impact ecosystem functioning at local to regional scales and these impacts must be considered for accurately assessing future implications of climate change.

Okun's law is a fundamental macroeconomic principle that reveals the negative relationship between the unemployment rate and economic growth. This study aims to analyze the validity of Okun's law using general, male, and female unemployment rates covering the period from 2005:Q1 to 2024:Q2 in the Turkish economy, along with Gross Domestic Product (GDP) variables calculated using the production, income, and expenditure methods. Within the methodological framework of the analysis, the Fractional Frequency Fourier ADF (FFFADF) unit root test was first applied to the variables, and then the validity of Okun's law between each GDP variable and each unemployment rate was examined separately using Wavelet Transform Coherence (WTC) analysis. The analysis results provided strong evidence that Okun's law is generally applicable in Türkiye. It has been determined that the relationship is most valid for GDP calculated by the production method, and least valid for the female unemployment rate. More pronounced negative relationships were observed between the male unemployment rate and GDP. These results show that growth and employment dynamics differ depending on the method of calculating GDP and the type of unemployment. In light of the findings, while the role of policies supporting economic growth in reducing unemployment is confirmed, it is emphasized that employment policies, particularly those targeting the male labor force, can have a more pronounced positive impact on GDP, and these dynamics should be considered in policy design.

We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multi-fractal behavior.

Both of Wavelet and Fast Fourier Transform are strong signal processing tools in the field of Data Analysis. In this paper fast fourier transform (FFT) and Wavelet Transform are employed to observe some important features of Solar image (December, 2004). We have tried to find out the periodicity and coherence of different sections of the solar image. We plotted the distribution of energy in solar surface by analyzing the solar image with scalograms and 3D-coefficient plots.

We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multi-fractal behavior.

Precise measurements of the anisotropies in the cosmic microwave background enable us to do an accurate study on the form of the primordial power spectrum for a given set of cosmological parameters. In a previous paper [1], we implemented an improved (error sensitive) Richardson-Lucy deconvolution algorithm on the measured angular power spectrum from the first year of WMAP data to determine the primordial power spectrum assuming a concordance cosmological model. This recovered spectrum has a likelihood far better than a scale invariant, or, 'best fit' scale free spectra (∆ ln L ≈ 25 w.r.t. Harrison Zeldovich, and, ∆ ln L ≈ 11 w.r.t. power law with ns = 0.95). In this paper we use Discrete Wavelet Transform (DWT) to decompose the local features of the recovered spectrum individually to study their effect and significance on the recovered angular power spectrum and hence the likelihood. We show that besides the infra-red cut off at the horizon scale, the associated features of the primordial power spectrum around the horizon have a significant effect on improving the likelihood. The strong features are localised at the horizon scale.

We have studied periodicities and correlation properties of tree ring width chronology of deodar tree from Joshimath (1584 -1999 years) and Uttarkashi (1500 -2002 years) in the western Himalayas and the pre-monsoon (March-April-May) temperature anomalies (1876 -2003) relative to 1961 -1990 mean, through wavelet analysis. Periodic behavior is observed in the tree ring chronology with periodicity in the form 11, 22, and 42 years. The analysis of the self-similar nature reveals longrange correlation with a Hurst exponent, H > 0.5. These are anti-correlated with the temperature anomalies. An interesting inversion behavior is observed around the year 1750. The power spectral analysis of the time series corroborate the results of wavelet method.

We consider the space h ∞ v of harmonic functions in R n+1 , where the weight v satisfies the doubling condition. Boundary values of functions in h ∞ v are characterized in terms of their smooth multiresolution approximations. The characterization yields the isomorphism of Banach spaces h ∞ v ∼ l ∞ . The results are also applied to obtain the law of the iterated logarithm for the oscillation of functions in h ∞ v along vertical lines.

Việt Nam đã nhận được đầu tư trực tiếp nước ngoài đáng kể trong vài thập kỷ qua cùng với chính sách tăng trưởng xanh và phát triển bền vững đang được Chính phủ quan tâm. Tăng trưởng kinh tế (GDP), FDI, toàn cầu hóa (GLO) và tăng trưởng xanh (GG) có thể ảnh hưởng đến chất lượng môi trường. Nghiên cứu này nhằm mục tiêu đánh giá tác động của FDI, toàn cầu hóa, tăng trưởng kinh tế và tăng trưởng xanh đến lượng khí thải CO2 ở Việt Nam giai đoạn 1998-2022 bằng phân tích wavelet. Kết quả chỉ ra rằng FDI, GG và GLO tác động tích cực đến chất lượng môi trường ở các tần số và thời gian khác nhau. Đặc biệt, trong ngắn hạn và trung hạn, GDP ảnh hưởng tích cực đến lượng khí thải CO2, trong khi đó chúng lại ảnh hưởng tiêu cực đến lượng khí thải CO2 trong dài hạn. Nhìn chung phân tích wavelet cho thấy GLO, GG và FDI không cải thiện môi trường ở Việt Nam trong ngắn hạn. Vì vậy, Chính phủ nên cung cấp các biện pháp khuyến khích tăng trưởng xanh, toàn cầu hóa để tăng dòng vốn FDI sử dụng năng lượng tái tạo trong sản xuất.

Nghiên cứu này nhằm đánh giá tác động của FDI, đổi mới công nghệ (TEC), tài nguyên thiên nhiên (NAR), công nghiệp hóa (IDV) đến tăng trưởng kinh tế (GDP) tại Việt Nam giai đoạn 1986-2022. Để ước lượng mối quan hệ phức tạp này, mô hình hồi qui phân vị và kiểm định nhân quả quang phổ được sử dụng nhằm phân tích tác động của các biến độc lập lên biến phụ thuộc trên các điều kiện kinh tế và tần số khác nhau. Kết quả cho thấy, phần lớn phân vị của các biến nghiên cứu, FDI, TEC, NAR, IDV tác động dương đến tăng trưởng kinh tế tại Việt Nam. Hơn nữa, kiểm định nhân quả Granger cũng cho rằng tồn tại mối quan hệ hai chiều giữa các biến nghiên cứu trên các tần số khác nhau. Kết quả này cung cấp thông tin hữu ích cho nhà chính sách hoạch định chiến lược ngắn hạn và dài hạn nhằm đạt phát triển kinh tế ổn định.

The COVID-19 outbreak prompts the need for new ways to detect and prevent epidemics. Since cough is one of the COVID-19 symptoms, our work proposes a sound recognition system based on our previous works which are able to detect different type of cough through a continuously home sound analysis. It is a part of EpiSemioWatch AMI COVID UTC funded project which aims to develop a detection system of epidemic risk in retirement home using sound and movement sensors. This paper presents the sound part of the global system and more explicitly the differentiation of cough from other environmental sound. The proposed system detects automatically the sound activity through a wavelet based system, realize an acoustic segmentation speech/sound and classify the cough sounds. A first evaluation of the system in our lab is presented.

Our prior studies indicated that postural fainting relates to thoracic hypovolemia. A supranormal increase in initial vascular resistance was sustained by increased peripheral resistance until late during head-up tilt (HUT), whereas splanchnic resistance, cardiac output, and blood pressure (BP) decreased throughout HUT. Our aim in the present study was to investigate the alterations of baroreflex activity that occur in synchrony with the beat-to-beat time-dependent changes in heart rate (HR), BP, and total peripheral resistance (TPR). We proposed that changes of low-frequency Mayer waves reflect sympathetic baroreflex. We used DWT multiresolution analyses to measure their time dependence. We studied 22 patients, 13 to 21 yr old, 14 who fainted within 10 min of upright tilt (fainters) and 8 healthy control subjects. Multiresolution analysis was obtained of continuous BP, HR, and respirations as a function of time during 70° upright tilt at different scales corresponding to frequency ...

An earthquake of magnitude 6.4 (Mw) struck the city of Bingöl in eastern Turkey on 1 May 2003, resulting in 168 deaths and extensive damage to private and public buildings. A US team of researchers and engineers from Purdue University, the University of Kansas, and WJE Associates Inc. sponsored by the National Science Foundation (NSF) was on the ground within a week of the earthquake to survey the damage. The US team collaborated with researchers from the Middle East Technical University (METU). A joint report sponsored by the NSF (US) and TUBITAK (Turkey) summarizes the results of their observations. This paper focuses on the damage to 23 reinforced concrete schools and 4 dormitories. The sample includes 2, 3 and 4story moment-frame structures, some with only masonry infill walls and others with both masonry infill walls and reinforced concrete shear walls. The geotechnical and geological observations indicated that any variation in the shaking at the different schools was not likely to have been affected strongly by the soil conditions and noted the absence of foundation failures. The quality of construction materials, workmanship, detailing practices and inspection level can be considered uniform throughout the entire building sample. These observations provide a unique opportunity to study the structural performance of the schools where various levels of damage were observed. The noted damage ranged from light to complete collapse of the first story. The number of stories, type of the structural system, ratio of reinforced concrete column and wall areas to the overall floor area, and proximity of the schools to the epicenter were selected to be the major study parameters. Regardless of the school type, total collapse was prevented if reinforced concrete shear walls were present because they compensated for the vulnerability of the captive columns effectively shortened by masonry walls. In the schools with heavy damage, captive columns were found to be the main cause of poor performance. The salient feature of the structural damage in Bingöl was defined by the varying interaction, ranging from good to very bad, of the tile masonry with reinforced concrete frames.

El principal objetivo de este trabajo es describir detalladamente el comienzo del Monzón Sudamericano utilizando datos de precipitación disponibles en la zona tropical y subtropical de Sudamérica. El análisis fue comparado con el realizado utilizando datos de radiación saliente de onda larga (OLR), con el fin de evaluar la eficiencia de los datos de lluvia para detectar los principales patrones de la evolución del monzón durante la primavera austral. Los resultados muestran que tanto la OLR como la precipitación describen bien el desplazamiento de la convección desde el noroeste hacia el sudeste en el centro de Brasil a principios de octubre. La comparación de diferentes metodologías para establecer fechas de comienzo de la estación lluviosa muestran que el método de , basado en la evolución de OLR, indica el comienzo del monzón en casi toda Sudamérica sin necesitar adaptación para cada región, tal como ocurre con los métodos basados en la precipitación. Los campos medios muestran que la lluvia en Brasil central comienza y se incrementa moderadamente, manteniéndose con valores menores a los observados en el noroeste y sudeste de la región tropical. Posteriormente, un abrupto cambio en la magnitud de la precipitación tiene lugar, en promedio tres péntadas después del inicio de la estación lluviosa, en Brasil central aunque similares cambios se observan en toda la región tropical. Se sugiere que la actividad de los transientes, que ocurre en el comienzo de la estación de lluvia cuando la inestabilidad aumenta y se aproximan las condiciones de verano, es uno de los factores que inciden en el desarrollo de este cambio abrupto en la precipitación. La caracterización de los incrementos en la lluvia provee información complementaria que puede ser utilizada adicionalmente a la fecha de inicio de la misma.

Accurate fetal R-peak detection from low-SNR fetal electrocardiogram (FECG) signals remains a critical challenge as current NI-FECG methods struggle to extract high SNR FECG signals and conventional algorithms fail when signal quality deteriorates. We proposed a U-Net-based method that enables robust R-peak detection directly from low-SNR FECG signals (0-12 dB), bypassing the need for high-SNR inputs that are clinically difficult to acquire. The method was evaluated on both real (A&D FECG) and synthetic (FECGSYN) databases, comparing against ten state-of-the-art detectors. The proposed method significantly reduces false predictions compared to commonly used detection algorithms, achieving a PPV of 99.81%, an SEN of 100.00%, and an F1-score of 99.91% on the A&D FECG database and a PPV of 99.96%, an SEN of 99.93%, and an F1-score of 99.94% on the FECGSYN database. Further investigation of robustness in low-SNR conditions (0 dB, 5 dB, and 10 dB) achieved 87.38% F1-score at 0 dB SNR on real signals, surpassing the best-performing algorithm implemented in Neurokit by 13.58%. In addition, the algorithm showed ≤2.65% performance variation across tolerance windows (50 reduced to 20 ms), further underscoring its detection accuracy. Overall, this work reduces the reliance on high-SNR FECG signals by reliably extracting R-peaks from suboptimal signals, providing implications for the reliability of fetal heart rate variability analysis in real-world noisy environments.

Electrocardiography (ECG) is a promising approach for continuous fetal heart rate monitoring. Its morphology can provide information on fetal health to guide patient care by clinicians. However, fetal ECGs extracted from abdominal ECGs are often too weak to reliably detect fetal heart rate. This study evaluates the application of a U-Net architecture for accurate R-peak detection in low-SNR fetal ECG signals. The proposed method achieves high accuracy with a positive predictive value of 99.81%, sensitivity of 100.00%, and an F1-score of 99.91% on direct fetal ECG from the Abdominal and Direct ECG Database, with significantly reduced false predictions, and outperforming two other baseline methods compared with. Notably, our approach demonstrates robustness, accurately predicting peaks in regions of high distortion, a capability unmatched by other methods evaluated. This finding indicates the suitability and benefits of the U-Net architecture for peak detection in fetal ECG signals.

We examined statistical correlations between the frequencies of seven proposed nucleosome positioning motifs and the densities of repetitive sequences in the human genome. For both parametric and non-parametric measures of statistical correlations there is a tendency for repetitive sequence density to be negatively correlated with the density of R/Y-based nucleosome positioning motifs, while being positively correlated with that of W/S-based motifs. These results largely hold even when motifs are examined only within repeat-filtered sequences. The RRRRRYYYYY motif and its 5-base shift YYYYYRRRRR, in particular, is over-represented in the human genome; and its negative correlation is consistently present at different regions and at different length scales. For some other nucleosome positioning motifs, the relationship with repeats can be regional or length scale dependent. Considering the importance of nucleosome formation in epigenetic regulations, these results may provide new insight to the evolution of repetitive sequences.

Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Results. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Results indicate that the proposed method is better in terms of efficiency analyzed. Conclusion. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

Objective: Frequency properties of the EEG characteristics of different seizure types including absence seizures have been described for various rodent models of epilepsy. However, little attention has been paid to the frequency properties of individual spike-wave complexes (SWCs), the constituting elements charac

Abstract: A minimum between solar cycle 22 and 23 has been defined earlier on the basis of type-I radio burst only. In the present paper a re-visit to the occurrence of type-I radio bursts in relation to general level of solar activity (sunspot number) is made covering the minima ...

CONTENTS 1. Introduction 2. Rigorous Results about Conjugacies between Circle Maps 3. Some General Heuristic Remarks on Renormalization and Conjugacies 4. Computing the Conjugacies 5. Methods for Studying the Regularity 6. Numerical Implementation 7. Results 8. Some Bounds on the Regularity of Conjugacies 9. Conclusion Acknowledgments References

Atmospheric gravity wave induced airglow fluctuations of the hydroxyl OH Meinel and other bands are routinely observed using CCD imagers operating in the near infrared wavelength region. Farther into the infrared, the intensity of the OH emissions is much greater. Recently, a new IR imaging camera was modified for infrared viewing of the night sky with approximately 1 steradian field of view. The filter had a center wavelength of 1467 nm and a bandwidth of 177 nm to include components of the OH (Δv = 2) band. The images show good signal‐to‐noise ratios of 180 with 10 second exposures. Cross‐spectral and wavelet analysis were used to obtain spatial and temporal information about observed airglow fluctuations, and horizontal wavelengths and wave periods as short as 3.7 km and 3 min, respectively, were determined.

We are sometimes presented with data with serious flaws, like saturation, over-range, zero shifts, and impulsive noise, including much of the available pyrotechnic data. Obviously, these data should not be used if at all possible. However, we are sometimes forced to use these data as the only data available. A method to salvage these data using wavelets is discussed. The results must be accepted with the understanding that the answers are credible, not necessarily correct. None of the methods will recover information lost due to saturation and over-range with the subsequent nonlinear behavior of the data acquisition system. The results are illustrated using analytical examples and flawed pyrotechnic data.

切石亮,福原輝幸,森永啓詩,徳永ロベルト,高橋尚人: 冬季路面状態の評価技術に関する研究について,第 回寒地技術シンポジウム講演論文集, 後藤彰彦,加世田将光,北川和男,島村哲郎,大道賢, 土屋忠寛,石丸修,白石哲也:画像処理を用いた排水性 舗装路面の排水状況評価,自動車技術会学術講演会前刷 集, Johan Casselgren, Michael Sjödahl, James LeBlanc: Angular spectral response from covered asphalt, Applied Optics, Vol.46, No.20, p. 4277-4288(2007) Massimo Bertozzi, Rean Isabella Fedriga, Carlo D’Ambrosio: Adverse Driving Conditions Albert: Investigations on the SWIR Bandwidth for Road Status Monitoring, ICIAP 2013, Part I, LNCS 8156, p. 592-601(2013) Johan Casselgren, Michael Sjödahl: Polarization resolved classification of winter road condition in the rear-infrared region, Applied Optics, Vol. 51, Issue 15, p. 3036-3045(2012) P. Pyykönen, M. Jokela, J. Birgitta, Martinkauppi, M. Kutila: Road friction monitoring, SIRWEC 2012 Helsinki, ID 0049, p. 1-6(2012) 二瓶光弥,清水健一,安藤泰之:氷路面の摩擦痕断面形 状計測によるタイヤ 氷摩擦の解析,自動車技術会論文 集, , , 城戸章宏:レーザによる各種路面の光学特性計測に関す る研究-第 報 画像処理による計測-,北海道自動車 短期大学研究紀要,第 号, 城戸章宏:凍結路面における摩擦係数μの非接触計測, 日本機械学会北海道支部第 回講演会講演概要集,

The work offers the methods for invariant representation of images against a variety of distorting factors including 2D and 3D rotation, changes in brightness, contrast and scale. It also deals with the procedure of recursive contour preparation consisting of step-by-step preparation of differences among the pixels of grey-scale image and formation of positive, negative and zero preparations. Thus at the first step the contour preparation is effected for the first differences, at the second step, for the second differences, and so on, with a step-by-step definition of the criterial function of distribution of binarized preparations. So it is possible to identify objects in different lighting conditions which simplifies the implementation of similar approaches. This relative simplicity of this method extends the range of its possible application for recognition purposes and for its implementation in the parallel-hierarchical network in particular.

The work offers the methods for invariant representation of images against a variety of distorting factors including 2D and 3D rotation, changes in brightness, contrast and scale. It also deals with the procedure of recursive contour preparation consisting of step-by-step preparation of differences among the pixels of grey-scale image and formation of positive, negative and zero preparations. Thus at the first step the contour preparation is effected for the first differences, at the second step, for the second differences, and so on, with a step-by-step definition of the criterial function of distribution of binarized preparations. So it is possible to identify objects in different lighting conditions which simplifies the implementation of similar approaches. This relative simplicity of this method extends the range of its possible application for recognition purposes and for its implementation in the parallel-hierarchical network in particular.

SUMMARY. By means of the wavelet analysis of some data obtained by numerical simulations, we show the interplay between standard deformations and atomic rearrangements in quasicrystals, in particular around a crack in a four points bending test.

grapevine genotypes, analyse polymorphism level of ISSR primers used, and determine genetic relationship of some Azerbaijani, introduced cultivars and hybrids. Twenty-one cultivars were analysed via ten polymorphic ISSR primers.. Morphological and ampelography data of genotypes studied according OIV descriptors to provide complete information of accessions. ISSR primers produced a total of 56 bands of which 44 were polymorphic. Resolving power of the ISSR primers ranged between 1.61 (UBC 826) and 4.09 (UBC 840). PIC (Polymorphism Information Content) values varied from 0.211(UBC 842) to 0.401 (UBC 810) respectively. The grapevine genotypes were grouped into five major kinship groups. Considering morphological and high genetic similarity value Khalbasar and Apoi Khagog genotypes showed highest genetic similarity index (0.923) and could be theoretically identical. Our results revealed that ISSR genetic markers combined with morphological and ampleography data could be a better tool for evaluation of genetic diversity among the grapevine genotypes.

Number of samples PSNR PSNR as a function of number of samples Pseudo-random sampling Quasi-random sampling TOTAL VARIATION MINIMIZATION QUASI-RANDOM SAMPLING 2nd order SFC 3rd order SFC 1st order SFC Coordinates of the golden ratio sequence (below) are transformed from the unit interval to the unit square with the Hilbert space filling curve.

Video sequences in TV and surveillance systems usually contain noise which decreases the visual quality and the performance of various post-processing tasks in the video chain. Usually only white Gaussian noise is assumed within these video application. However in practice that assumption does not always hold and results in poor denoising performance of standard video enhancement algorithm. In order to solve these problems we propose a new adaptive wavelet-based video denoising method. The method consist of a ...

We characterize the interrelation of CO 2 prices with energy prices (gas and electricity), and with economic activity. Previous studies have relied on time-domain techniques, such as Vector Auto-Regressions. In this study, we use multivariate wavelet analysis, which operates in the time-frequency domain. Wavelet analysis provides convenient tools to distinguish relations at particular frequencies and at particular time horizons. Our empirical approach has the potential to identify relations getting stronger and then disappearing over specific time intervals and frequencies. We are able to examine the coherency of these variables and lead-lag relations at different frequencies for the time periods in focus.

Spectral analysis and ARMA models have been the most established weapons of choice for the detection of cycles in time series data. However, such techniques are only appropriate when periodic components are time invariant. This has led some scholars to disregard the possibility of irregular cycles. We aim to contribute to further reconsideration of the possibility of cycles in political phenomena by introducing wavelet analysis. Its main contribution comes from the ability to estimate the spectral characteristics of a time series as a function of time, thus revealing how its different periodic components change over time, while preserving rigorous standards of statistical inference. We demonstrate the usefulness of wavelet analysis with two applications. The first concerns the possibility of long-cycles in wars, one of the central puzzles in the international relations sub-field. The second concerns election returns in presidential and congressional elections in the United States, where the existence of cyclical patterns has been equally controversial. Contrary to the prevailing wisdom, wavelet analysis allows the detection of transient and coexisting cycles, shedding some light over phenomena that have remained unaddressed so far. * We thank Bernard Cazelles for providing us the code used in and Joshua Goldstein for the data used in . We also thank Paul Beck and Nathan Kelly for valuable comments and suggestions. The usual disclaimer applies.

The structural integrity of pile foundations is critical for the safety and longevity of buildings and infrastructure. Low strain impact testing is a widely used non-destructive method for assessing pile length and identifying significant defects; however, its sensitivity to minor flaws remains limited. This study aims to enhance the detection capabilities of low strain testing for minor defects by proposing an improved methodology. We conducted field tests on ten piles with small, artificially introduced flaws and complemented these tests with three-dimensional numerical simulations. Initial timedomain analyses of both field and simulated data, using low-frequency wave excitation, did not reveal distinct signal features indicative of defects. To address this limitation, we employed a set of hammers with varying weights and head materials for wave excitation, simulated with different input force pulse durations. We further applied Complex Continuous Wavelet Transform (CCWT) for time-frequency analysis of the acquired signals, which effectively identified minor defects through characteristic changes in wavelet coefficient phase angles at expected timestamps. The consistency of CCWT phase spectrum features across signals from different hammers, considering the varying sensitivities of wave excitations, facilitates the differentiation of genuine flaw-induced phase shifts from noise. The study's findings were integrated into an improved low strain pile integrity testing workflow, enhancing the method's accuracy in detecting minor flaws.

OBJETIVO: Apresentar um sistema de extração de características de tempo e frequência do sinal EMG implementado no LabVIEW TM . MÉTODOS: Para o desenvolvimento deste sistema, implementou-se 16 características no domínio do tempo e 10 características no domínio da frequência na linguagem de programação do LabVIEW TM . RESULTADOS: A apresentação dos resultados se dá de maneira gráfica para quatro características escolhidas (MAV, ZC, SM 1 eMNF) para os movimentos de flexão e extensão. CONCLUSÕES: Através dos resultados obtidos, foi possível ver que há uma nítida separação do sinal nos movimentos de extensão e flexão. Além disso, a criação de sub-rotinas para extração de características do sinal EMG torna possível sua aplicação em outros sistemas e programas mais complexos. Apresenta-se como meta para trabalhos futuros o estudo da importância de cada característica para diferentes músculos e movimentos.

Background: Heart Failure is present in 1 out of 10 patients presenting Acute Coronary Syndrome. ECG predictors of reduced LVEF provide essential non-invasive triage capabilities, especially when echocardiography is not available instantly within reach. 12 lead ECG is easily accessible during the preliminary checkup of patient No direct comparison of the current electrocardiogram (ECG) interpretation program exists. Additional ECG training can improve accuracy. A systematic review and meta-analysis observed that across various training like pretraining and post-training and the median accuracy of ECG interpretation was 54% and 67% respectively [1]. Method: Here we proposed machine learning based approach to identify the highly predictive ECG Marker of Suspected Acute Coronary Syndrome i.e. the Ejection Fraction found in checkups [2]. This research proposes a modified technique for identifying cardiac abnormalities and QRS complexes, Leveraging Machine Learning and SVM (Support Vector Machine) classifiers. Results: The presented technique surpasses existing methods in both sensitivity and specificity achieving accuracy of 98.4 % for cardiac irregularities for the standard 12-Lead ECG Georgia database

Spike sorting plays a pivotal role in neuroscience, serving as a crucial step of separating electrical signals recorded from multiple neurons to further analyze neuronal interactions. This process involves separating electrical signals that originate from multiple neurons, recorded through devices like electrode arrays. This is a very important link in the field of brain-computer interfaces. The objective of spike sorting algorithm (SSA) is to distinguish the behavior of one or more neurons from background noise using the waveforms captured by brain-embedded electrodes. This article starts from the steps of the conventional SSA and divides the SSA into three steps: spike detection, spike feature extraction, and spike clustering. It outlines prevalent algorithms for each phase before delving into two emerging technologies: template matching and deep learning-based methods. The discussion on deep learning is further subdivided into three approaches: end-to-end solution, deep learning for spike sorting steps, and spiking neural networks-based solutions. Finally, it elaborates future challenges and development trends of SSAs.

A space-and time-adaptive two-dimensional multiresolution time-domain (MRTD) algorithm based on arbitrary resolutions of Battle-Lemarie wavelets is proposed. Analytic expressions for the finite-summation coefficients are derived and details concerning the modeling of hard boundaries, excitation, and field reconstruction are extensively discussed. Through the use of a combination of absolute and relative thresholding, a dynamically changing grid is developed with minimal computational requirements in comparison to the finite-difference time-domain technique. After the validation process, MRTD is used for the first time for the numerical optimization of complex RF structures such as evanescent-mode filters.

A brief description and the results of the temporal variability of the flare index over the epoch of almost 4 cycles (1966-2001) are presented. Using Fourier and wavelet transforms the long-term periodicities in the daily flare index data for the total surface and for the northern and the southern hemispheres of the Sun are presented. A significant variability was found for all periods. The wavelet transform results show that the occurrence of flare index power is highly intermittent in time.

In this work, a new on-line method for detecting incipient failures in electrical motors is proposed. The method is based on monitoring certain statistical parameters estimated from the analysis of the steady state stator current (for broken bars, saturation, eccentricities, and bearing failures) or the axial flux signal (for coil short-circuits in the stator windings). The approach is based on the extraction of the envelop of the signal by Hilbert transformation, pre-multiplied by a Tukey window to avoid transient distortion. Then a wavelet analysis (multi-resolution analysis) is performed, which makes the fault diagnosis easier. Finally, based on a statistical analysis, the failure thresholds are determined. Thus, by monitoring the mean value estimate it is possible to detect an incipient failure condition on the machine.

A wireless powered implantable atrial defibrillator consisting of a battery driven hand-held radio frequency (RF) power transmitter (ex vivo) and a passive (battery free) implantable power receiver (in vivo) that enables measurement of the intracardiac impedance (ICI) during internal atrial defibrillation is reported. The architecture is designed to operate in two modes: Cardiac sense mode (power-up, measure the impedance of the cardiac substrate and communicate data to the ex vivo power transmitter) and cardiac shock mode (delivery of a synchronised very low tilt rectilinear electrical shock waveform). An initial prototype was implemented and tested. In low-power (sense) mode, >5 W was delivered across a 2.5 cm air-skin gap to facilitate measurement of the impedance of the cardiac substrate. In high-power (shock) mode, >180 W (delivered as a 12 ms monophasic very-low-tilt-rectilinear (M-VLTR) or as a 12 ms biphasic very-low-tiltrectilinear (B-VLTR) chronosymmetric (6ms/6ms) amplitude asymmetric (negative phase at 50% magnitude) shock was reliably and repeatedly delivered across the same interface;

In this work, a new model that combines the concepts of wavelet transformation and subspace analysis tools, like Independent Component Analysis, Topographic Independent Component Analysis, and Independent Subspace Analysis, is developed for the purpose of defect detection in textile images. In previous works, it has been shown that reduction of the textural components of the textile image by preprocessing has increased the performance of the system. Based on this observation, in present work, the aforementioned subspace analysis tools are aimed to be applied on the sub-band images. The feature vector of a sub-window of a test image is compared with that of the defect-free image in order to make a decision. This decision is based on a Euclidean distance classifier. The performance increase that results using wavelet transformation prior to subspace analysis has been discussed in detail. While all the subspace analysis methods has been found to lead to the same detection performances, as a further step, independent subspace analysis is used to classify the detected defects according to their directionalities.

Over time, Spain has implemented various legislative measures to address the imbalance between homeownership and rental housing in a real estate market closely linked to the country's economic conditions. Changes in governance have introduced different regulatory approaches that may have influenced rental prices. This study examines the relationship between political uncertainty and rental housing prices in Spain from 1997 to 2024, using fractional integration, fractional cointegration, and wavelet analysis. The results indicate that exogenous shocks, such as uncertainty, temporarily affect rental prices. Additionally, a one-point increase in the Economic Policy Uncertainty index correlates with a 16.4-point rise in rental prices.

• We have fabricated cathode based on TiO x nanotubes decorated by RuO x nanowhiskers • Surface morphology of cathode is tailored to facilitate gas bubble detachment • A pre-dominant type of hydrogen bubble release is resolved using wavelet analysis • The best HER efficiency is up to 64% associated with small bubble detachment 4

P-adic numbers serve as the simplest ultrametric model for the tree-like structures arising in various physical and biological phenomena. Recently p-adic dynamical equations started to be applied to geophysics, to model propagation of fluids (oil, water, and oil-in-water and water-in-oil emulsion) in capillary networks in porous random media. In particular, a p-adic analog of the Navier–Stokes equation was derived starting with a system of differential equations respecting the hierarchic structure of a capillary tree. In this paper, using the Schauder fixed point theorem together with the wavelet functions, we extend the study of the solvability of a p-adic field analog of the Navier–Stokes equation derived from a system of hierarchic equations for fluid flow in a capillary network in porous medium. This equation describes propagation of fluid’s flow through Geo-conduits, consisting of the mixture of fractures (as well as fracture’s corridors) and capillary networks, detected by sei...

A space-and time-adaptive two-dimensional multiresolution time-domain (MRTD) algorithm based on arbitrary resolutions of Battle-Lemarie wavelets is proposed. Analytic expressions for the finite-summation coefficients are derived and details concerning the modeling of hard boundaries, excitation, and field reconstruction are extensively discussed. Through the use of a combination of absolute and relative thresholding, a dynamically changing grid is developed with minimal computational requirements in comparison to the finite-difference time-domain technique. After the validation process, MRTD is used for the first time for the numerical optimization of complex RF structures such as evanescent-mode filters.

The spatial variability of preferential pathways for water and chemical transport in a field soil, as visualized through dye infiltration experiments, was studied by applying multifractal and wavelet transform analysis (WTA). After dye infiltration into a 4 m 2 plot located on a Vertisol soil near College Station, Texas, horizontal planes in the subsoil were exposed at 5 cm intervals, and dye stain patterns were photographed. Box-counting methods and WTA were applied to all of the 16 digitalized high-resolution dye images and to the dye-mass image obtained merging all sections. The wellknown Devil's staircase multifractal was also used to illustrate wavelet-based analysis. Our results suggest that wavelet methods can complement box-counting analysis in the context of multiscaling structure analysis.