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Journal articles on the topic 'Spectral and temporal analysis'
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Narogan, M. V., G. V. Yatsyk, E. V. Syutkina, A. V. Masalov, and I. I. Malkova. "Spectral and spectral-temporal heart rate analysis in newborns." Human Physiology 33, no. 4 (2007): 433–40. http://dx.doi.org/10.1134/s0362119707040093.
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Zaveri, H. P., L. D. Iasemidis, J. C. Sackellares, W. J. Williams, and T. W. Hood. "Multichannel Spectral Analysis in Temporal Lobe Epilepsy." Journal of Clinical Neurophysiology 5, no. 4 (1988): 340. http://dx.doi.org/10.1097/00004691-198810000-00043.
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Berloff, P., and I. Kamenkovich. "On Spectral Analysis of Mesoscale Eddies. Part II: Nonlinear Analysis." Journal of Physical Oceanography 43, no. 12 (2013): 2528–44. http://dx.doi.org/10.1175/jpo-d-12-0233.1.
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Abstract Several turbulent flow regimes of an idealized ocean circulation model are systematically analyzed in physical and spectral domains. Zonal dispersion properties of transient mesoscale eddies are described by the zonal wavenumber/temporal frequency spectra. The eddy patterns and the corresponding nonlinear eddy forcing exerted on the jets are examined by filtering different parts of the spectra. Comparison of the outcome of this nonlinear analysis with the properties of the linearized solutions (obtained in Part I of this paper) demonstrates that a very substantial part of the flow dynamics is controlled by the underlying linear dynamics. This result supports the hypothesis that it is possible to describe most of the oceanic mesoscale eddies as a wave turbulence phenomenon.
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Cho, Yang-Jin, So-Yoen Kim, Mi Rang Son, Ho-Jin Son, Dae Won Cho, and Sang Ook Kang. "Time-resolved spectroscopic analysis of the light-energy harvesting mechanism in carbazole-dendrimers with a blue-phosphorescent Ir-complex core." Physical Chemistry Chemical Physics 19, no. 30 (2017): 20093–100. http://dx.doi.org/10.1039/c7cp01989k.
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Mayer, Dennis, Fabiano Lever, and Markus Gühr. "Data analysis procedures for time-resolved x-ray photoelectron spectroscopy at a SASE free-electron-laser." Journal of Physics B: Atomic, Molecular and Optical Physics 55, no. 5 (2022): 054002. http://dx.doi.org/10.1088/1361-6455/ac3c91.
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Abstract The random nature of self-amplified spontaneous emission (SASE) is a well-known challenge for x-ray core level spectroscopy at SASE free-electron lasers (FELs). Especially in time-resolved experiments that require a combination of good temporal and spectral resolution the jitter and drifts in the spectral characteristics, relative arrival time as well as power fluctuations can smear out spectral-temporal features. We present a combination of methods for the analysis of time-resolved photoelectron spectra based on power and time corrections as well as self-referencing of a strong photoelectron line. Based on sulfur 2p photoelectron spectra of 2-thiouracil taken at the SASE FEL FLASH2, we show that it is possible to correct for some of the photon energy drift and jitter even when reliable shot-to-shot photon energy data is not available. The quality of pump–probe difference spectra improves as random jumps in energy between delay points reduce significantly. The data analysis allows to identify coherent oscillations of 1 eV shift on the mean photoelectron line of 4 eV width with an error of less than 0.1 eV.
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Geoga, Christopher J., Charlotte L. Haley, Andrew R. Siegel, and Mihai Anitescu. "Frequency–wavenumber spectral analysis of spatio-temporal flows." Journal of Fluid Mechanics 848 (June 8, 2018): 545–59. http://dx.doi.org/10.1017/jfm.2018.366.
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We propose a fully spatio-temporal approach for identifying spatially varying modes of oscillation in fluid dynamics simulation output by means of multitaper frequency–wavenumber spectral analysis. One-dimensional spectrum estimation has proven to be a valuable tool in the analysis of turbulence data applied spatially to determine the rate of energy transport between spatial scales, or temporally to determine frequencies of oscillatory flows. It also allows for the quantitative comparison of flow characteristics between two scenarios using a standard basis. It has the limitation, however, that it neglects coupling between spatial and temporal structures. Two-dimensional frequency–wavenumber spectral analysis allows one to decompose waveforms into standing or travelling variety. The extended higher-dimensional multitaper method proposed here is shown to have improved statistical properties over conventional non-parametric spectral estimators, and is accompanied by confidence intervals which estimate their uncertainty. Multitaper frequency–wavenumber analysis is applied to a canonical benchmark problem, namely, a direct numerical simulation of von Kármán vortex shedding off a square wall-mounted cylinder with two inflow scenarios with matching momentum-thickness Reynolds numbers $Re_{\unicode[STIX]{x1D703}}\approx 1000$ at the obstacle. Frequency–wavenumber analysis of a two-dimensional section of these data reveals that although both the laminar and turbulent inflow scenarios show a turbulent $-5/3$ cascade in wavenumber ($\unicode[STIX]{x1D708}$) and frequency ($f$), the flow characteristics differ in that there is a significantly more prominent discrete harmonic oscillation near $(f,\unicode[STIX]{x1D708})=(0.2,0.21)$ in wavenumber and frequency in the laminar inflow scenario than the turbulent scenario. This frequency–wavenumber pair corresponds to a travelling wave with velocity near one near the centre path of the vortex street.
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Zhang, Yi-Qing, Xiang Li, and Athanasios V. Vasilakos. "Spectral Analysis of Epidemic Thresholds of Temporal Networks." IEEE Transactions on Cybernetics 50, no. 5 (2020): 1965–77. http://dx.doi.org/10.1109/tcyb.2017.2743003.
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ROWLEY, CLARENCE W., IGOR MEZIĆ, SHERVIN BAGHERI, PHILIPP SCHLATTER, and DAN S. HENNINGSON. "Spectral analysis of nonlinear flows." Journal of Fluid Mechanics 641 (November 18, 2009): 115–27. http://dx.doi.org/10.1017/s0022112009992059.
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We present a technique for describing the global behaviour of complex nonlinear flows by decomposing the flow into modes determined from spectral analysis of the Koopman operator, an infinite-dimensional linear operator associated with the full nonlinear system. These modes, referred to as Koopman modes, are associated with a particular observable, and may be determined directly from data (either numerical or experimental) using a variant of a standard Arnoldi method. They have an associated temporal frequency and growth rate and may be viewed as a nonlinear generalization of global eigenmodes of a linearized system. They provide an alternative to proper orthogonal decomposition, and in the case of periodic data the Koopman modes reduce to a discrete temporal Fourier transform. The Arnoldi method used for computations is identical to the dynamic mode decomposition recently proposed by Schmid & Sesterhenn (Sixty-First Annual Meeting of the APS Division of Fluid Dynamics, 2008), so dynamic mode decomposition can be thought of as an algorithm for finding Koopman modes. We illustrate the method on an example of a jet in crossflow, and show that the method captures the dominant frequencies and elucidates the associated spatial structures.
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Devi, A. Senorita. "Spectral and Temporal Properties of CXOUJ122956.7+075728 (ULX-1), an Ultraluminous X-Ray Source in NGC 4472." East European Journal of Physics, no. 1 (March 5, 2024): 95–101. http://dx.doi.org/10.26565/2312-4334-2024-1-07.
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This report presents a comprehensive analysis of the spectral and temporal characteristics of a highly significant Ultraluminous X-ray Source (ULX) designated as CXOUJ122956.7+075728 (ULX-1) situated in the elliptical galaxy NGC 4472 within the Virgo cluster. ULX-1 exhibits a soft spectral state, featuring a cool accretion disk component with kTin ∼ 0.15 keV, accompanied by a power-law tail displaying a steep power-law photon index, Γ ∼ 2.8. The spectral findings strongly support an estimated black hole mass of approximately 3.30 × 103 M⊙ under an isotropic emission model, and around 1.47 × 103 M⊙ in an extreme beaming scenario. Temporally, ULX-1 displays significant variability on time scales of 0.5, 1, and 2 ks, suggesting the possibility of instabilities within the accretion disk contributing to this behavior. However, despite this temporal variability, the power spectra analysis of this soft ULX reveals no signatures of pulsations, distinguishing it from certain pulsating ULXs (PULXs) typically associated with neutron stars. This absence of pulsations in ULX-1 further underscores its unique spectral and temporal characteristics within the broader context of ULX phenomena.
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Lopez-Fornieles, Eva, Guilhem Brunel, Nicolas Devaux, Jean-Michel Roger, James Taylor, and Bruno Tisseyre. "Application of Parallel Factor Analysis (PARAFAC) to the Regional Characterisation of Vineyard Blocks Using Remote Sensing Time Series." Agronomy 12, no. 10 (2022): 2544. http://dx.doi.org/10.3390/agronomy12102544.
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Monitoring wine-growing regions and maximising the value of production based on their region/local specificities requires accurate spatial and temporal monitoring. The increasing amount and variability of information from remote sensing data is a potential tool to assess this challenge for the grape and wine industry. This article provides a first insight into the capacity of a multiway analysis method applied to Sentinel-2 time series to assess the value of simultaneously considering spectral and temporal information to highlight site-specific canopy evolution in relation to environmental factors and management practices, which present a large diversity at this regional scale. Parallel Factor Analysis (PARAFAC) was used as an unsupervised technique to recover pure spectra and temporal signatures from multi-way spectral imagery of vineyards in the Languedoc-Roussillon region in the south of France. The model was developed using a time series of Sentinel-2 satellite imagery collected over 4978 vineyard blocks between May 2019 and August 2020. From the Sentinel-2 (spectral and temporal) signal, the PARAFAC analysis allowed the identification of spectral and temporal profiles in the form of pure components, which corresponded to vegetation and soil. The PARAFAC analysis also identified that two of the pure spectra were strongly related to characteristics and dynamics of vineyard cultivation at a regional scale. A conceptual framework was proposed in order to simultaneously consider both vegetation and soil profiles and to summarise the mass of data accordingly. This methodology allowed the computation of a concentration index that characterised how close a field was to a vegetation or a soil profile over the season. The concentration indices were validated for the vegetation and the soil over two growing seasons (2019 and 2020) with geostatistical analysis. A non-random distribution of the concentration index at the regional scale was assumed to highlight a strongly spatially organised phenomenon related to spatially organised environmental factors (soil, climate, training system, etc.). In a second step, spatial patterns of indices were subjected to the expertise of a panel of advisors of the wine industry in order to validate them in relation to vine-growing conditions. Results showed that the introduction of the PARAFAC method opened up the possibility to identify relevant spectro-temporal profiles for vine monitoring purposes.
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Souza, Pamela E., Richard A. Wright, Michael C. Blackburn, Rachael Tatman, and Frederick J. Gallun. "Individual Sensitivity to Spectral and Temporal Cues in Listeners With Hearing Impairment." Journal of Speech, Language, and Hearing Research 58, no. 2 (2015): 520–34. http://dx.doi.org/10.1044/2015_jslhr-h-14-0138.
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Purpose The present study was designed to evaluate use of spectral and temporal cues under conditions in which both types of cues were available. Method Participants included adults with normal hearing and hearing loss. We focused on 3 categories of speech cues: static spectral (spectral shape), dynamic spectral (formant change), and temporal (amplitude envelope). Spectral and/or temporal dimensions of synthetic speech were systematically manipulated along a continuum, and recognition was measured using the manipulated stimuli. Level was controlled to ensure cue audibility. Discriminant function analysis was used to determine to what degree spectral and temporal information contributed to the identification of each stimulus. Results Listeners with normal hearing were influenced to a greater extent by spectral cues for all stimuli. Listeners with hearing impairment generally utilized spectral cues when the information was static (spectral shape) but used temporal cues when the information was dynamic (formant transition). The relative use of spectral and temporal dimensions varied among individuals, especially among listeners with hearing loss. Conclusion Information about spectral and temporal cue use may aid in identifying listeners who rely to a greater extent on particular acoustic cues and applying that information toward therapeutic interventions.
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Hamarbitan, N. S., and G. F. Margrave. "Spectral analysis of a ghost." GEOPHYSICS 66, no. 4 (2001): 1267–73. http://dx.doi.org/10.1190/1.1487074.
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A seismic line was shot such that the source‐ghost effect from two different dynamite source patterns could be compared. Two 15‐shot seismic datasets were created that were identical in all respects except that one used 4 kg of explosives in a single 18‐m hole, while the other used 2 kg of explosives in each of two 9‐m holes. After identical processing, the final stacked sections of the 18‐m and 9‐m datasets are dramatically different in character and temporal resolution. An f‐x spectral analysis of the stacked sections reveals that the 18‐m data shows a loss in power and phase coherence from 45 to 58 Hz, while the 9‐m data shows a similar effect from 65 to 78 Hz. A spectral notch, centered near 55 Hz, due to a source ghost is suggested as the reason for the lower power in the 18‐m dataset. The 9‐m data is consistent with a spectral notch at a higher central frequency near 72 Hz. Above its spectral notch, 18‐m data shows a reemergence of weak signal that persists to near 80 Hz; the 9 m dataset shows little signal above 65 Hz. Examination of raw shot records shows that these effects are very difficult to observe in field records. Without specialized deghosting, the 9‐m dataset shows greater temporal resolution; however, the 18‐m dataset has a broader signal bandwidth and is potentially superior.
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Valiveti, Hima Bindu, Anil Kumar B., Lakshmi Chaitanya Duggineni, Swetha Namburu, and Swaraja Kuraparthi. "Soft computing based audio signal analysis for accident prediction." International Journal of Pervasive Computing and Communications 17, no. 3 (2021): 329–48. http://dx.doi.org/10.1108/ijpcc-08-2020-0120.
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Purpose Road accidents, an inadvertent mishap can be detected automatically and alerts sent instantly with the collaboration of image processing techniques and on-road video surveillance systems. However, to rely exclusively on visual information especially under adverse conditions like night times, dark areas and unfavourable weather conditions such as snowfall, rain, and fog which result in faint visibility lead to incertitude. The main goal of the proposed work is certainty of accident occurrence. Design/methodology/approach The authors of this work propose a method for detecting road accidents by analyzing audio signals to identify hazardous situations such as tire skidding and car crashes. The motive of this project is to build a simple and complete audio event detection system using signal feature extraction methods to improve its detection accuracy. The experimental analysis is carried out on a publicly available real time data-set consisting of audio samples like car crashes and tire skidding. The Temporal features of the recorded audio signal like Energy Volume Zero Crossing Rate 28ZCR2529 and the Spectral features like Spectral Centroid Spectral Spread Spectral Roll of factor Spectral Flux the Psychoacoustic features Energy Sub Bands ratio and Gammatonegram are computed. The extracted features are pre-processed and trained and tested using Support Vector Machine (SVM) and K-nearest neighborhood (KNN) classification algorithms for exact prediction of the accident occurrence for various SNR ranges. The combination of Gammatonegram with Temporal and Spectral features of the validates to be superior compared to the existing detection techniques. Findings Temporal, Spectral, Psychoacoustic features, gammetonegram of the recorded audio signal are extracted. A High level vector is generated based on centroid and the extracted features are classified with the help of machine learning algorithms like SVM, KNN and DT. The audio samples collected have varied SNR ranges and the accuracy of the classification algorithms is thoroughly tested. Practical implications Denoising of the audio samples for perfect feature extraction was a tedious chore. Originality/value The existing literature cites extraction of Temporal and Spectral features and then the application of classification algorithms. For perfect classification, the authors have chosen to construct a high level vector from all the four extracted Temporal, Spectral, Psycho acoustic and Gammetonegram features. The classification algorithms are employed on samples collected at varied SNR ranges.
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Gonzalez, A. G., L. C. Gallo, P. Kosec, et al. "Characterizing continuum variability in the radio-loud narrow-line Seyfert 1 galaxy IRAS 17020+4544." Monthly Notices of the Royal Astronomical Society 496, no. 3 (2020): 3708–24. http://dx.doi.org/10.1093/mnras/staa1735.
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ABSTRACT We present results of temporal and spectral analyses on four XMM–Newton EPIC pn observations of IRAS 17020+4544, a narrow-line Seyfert 1 galaxy with evidence of a radio jet. Analysis of the light curves reveals that this radio-loud source does not behave like the bulk population of its radio-quiet counterparts. A trend of spectral hardening with increased flux is found. Variability is found to increase with energy, though it decreases as the spectrum hardens. The first 40 ks of the most recent observation behave uniquely among the epochs, exhibiting a softer spectral state than at any other time. Possible non-stationarity at low energies is found, with no such effect present at higher energies, suggesting at least two distinct spectral components. A reverberation signature is confirmed, with the lag-frequency, lag-energy, and covariance spectra changing significantly during the soft-state epoch. The temporal analysis suggests a variable power law in the presence of a reflection component, thus motivating such a fit for the 0.3−10 keV EPIC pn spectra from all epochs. We find an acceptable spectral fit using the timing-motivated parameters and report the detection of a broad Fe K emission line, requiring an additional model component beyond the reflection spectrum. We discuss links between this source and other narrow-line Seyfert 1 sources that show evidence of jet activity, finding similarities among this currently very limited sample of interesting objects.
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Gorbunov, Yu N. "Stochastic signal processing in adaptive measurement systems with rough space-time statistics: invertible spectral analysis method." Izmeritel`naya Tekhnika 74, no. 2 (2025): 88–96. https://doi.org/10.32446/0368-1025it.2025-2-88-96.
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A modified method for efficient spectral and correlation-based spatio-temporal signal processing is presented, designed for operation under conditions of high dynamic variability in input signal intensity and varying frequency-time resources of digital processing. The method is based on adapting algorithms and refining the goals and tasks of signal processing. A methodology has been developed to achieve high instrumental resolution of signals based on spectral and/or correlation features. The study addresses aspects of improving the efficiency of spatio-temporal signal processing, which are relevant for radio engineering measurement systems with digital phased antenna arrays and moving target selection systems. The previously proposed adaptive method of reversible spectral analysis, developed by the author, has been modernized for use in spatio-temporal signal processing. The updated method takes into account the variability (type changes) of processed signals and introduces measures to reduce the dynamic range requirements of the input signal stream by utilizing coarse (low-bit and binary) statistics. The frequency nomenclature has been expanded to include temporal and spatial spectra of distribution laws (characteristic functions). Technical (hardware and software) constraints, such as the use of coarse signal quantization, are also considered. Processing efficiency is achieved through the application of a whitening operation (rejection of dominant components) for passive interference prior to the main stage – the reversible spectral analysis method — and through the use of traditional stochastic algorithms. This includes increasing sample sizes (apertures, windows) and improving the convergence rate of measurements in the basic Monte Carlo method. The results obtained can be applied in radio engineering measurement complexes, including radar systems, for tasks such as radio and radio technical monitoring, as well as for measuring range and bearing coordinates.
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RASHID, Haroon Ur, and Abdul Qadir KHAN. "A Phonemic and Acoustic Analysis of Hindko Fricatives." Acta Linguistica Asiatica 4, no. 3 (2015): 71–81. http://dx.doi.org/10.4312/ala.4.3.71-81.
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The Hindko language is mainly spoken in the province of Khyber Pukhtunkhaw, Pakistan. It relates to the Indo-Aryan family of languages. This paper focusses on the phonemic and acoustic analysis of Hindko fricatives. The phonemic analysis identifies that Hindko has eight fricatives. The acoustic analysis aims to explore temporal and spectral characteristics of these fricatives. The acoustic analysis discloses that Hindko fricatives are distinguishable on the basis of the temporal properties such as friction duration and spectral cues like turbulence noise.
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Tavabi, Kambiz, David Embick, and Timothy P. L. Roberts. "Spectral–temporal analysis of cortical oscillations during lexical processing." NeuroReport 22, no. 10 (2011): 474–78. http://dx.doi.org/10.1097/wnr.0b013e3283476b84.
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Latcu, Gabriel Decebal, Olivier Meste, Alexandre Duparc, et al. "Temporal and spectral analysis of ventricular fibrillation in humans." Journal of Interventional Cardiac Electrophysiology 30, no. 3 (2011): 199–209. http://dx.doi.org/10.1007/s10840-010-9541-1.
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Chang, Ching-Min, and Hund-Der Yeh. "Spectral analysis of temporal non-stationary rainfall-runoff processes." Journal of Hydrology 559 (April 2018): 84–88. http://dx.doi.org/10.1016/j.jhydrol.2018.02.017.
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Pang, Lihua, Xilin Liu, Yang Zhang, Qiaofeng Wang, Jiandong Li, and Xiao Liang. "Channel Correlation Analysis by Exploiting Temporal-Spectral-Spatial Information." Chinese Journal of Electronics 24, no. 2 (2015): 379–87. http://dx.doi.org/10.1049/cje.2015.04.026.
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Rigozo, Nivaor Rodolfo, and Adriano Petry. "THE ATMOSPHERIC PRESSURE EFFECT ON MUON DATA NORMALIZATION BY SPECTRAL ANALYSIS STUDIES." Revista Brasileira de Geofísica 31, no. 3 (2013): 507. http://dx.doi.org/10.22564/rbgf.v31i3.324.
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ABSTRACT. This paper presents a study of the atmospheric pressure effects on ground cosmic ray muon time series, using the iterative regression spectral analysis method. Along the study, it was observed that the 34 periods present in the atmospheric pressure amplitude spectrum are present in the muon data amplitude spectra as well. It was concluded that the normalization of muon data is only efficient for periods shorter than nine days, in order to eliminate the atmospheric effects.Keywords: cosmic rays, time series, spectral analysis. RESUMO. Este artigo apresenta um estudo dos efeitos da pressão atmosférica nas series temporais de raios cósmicos, usando a metodologia da análise espectral pela iteração regressiva. Foi observado um total de 34 periodicidades presentes no espectro de amplitude da pressão atmosférica que também estão presentes no espectro de amplitude dos dados de muons. Conclui-se que a padronização dos dados de muons para eliminar os efeitos da pressão atmosférica é eficiente somente para períodos abaixo de 9 diasPalavras-chave: raios cósmicos, série temporal, análise espectral.
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Noriega, N., E. F. Cárdenas, J. A. Chacón, and N. Vásquez. "Temporal Estimators of Peculiar GRBs." Journal of Physics: Conference Series 2796, no. 1 (2024): 012001. http://dx.doi.org/10.1088/1742-6596/2796/1/012001.
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Abstract In our study, we analyze four peculiar Gamma-Ray Bursts (GRBs), namely GRB070724A, GRB070429B, GRB090426, and GRB120804A, all detected by the Swift space telescope. The focus of our investigation lies in evaluating the temporal estimators, such as emission time and spectral lag time in the third Swift GRB catalog sample. Our findings reveal that the calculated temporal estimators offer diverse insights into the classification of the examined GRBs, hinting at the distinctive nature of these events. This suggests that these GRBs can be considered as ‘peculiar’ when compared to standard GRBs in the spectral plane, specifically in the Amati-like relation. Whereas, the spectral lag analysis of the four GRBs increases the evidence to consider these as ‘peculiar’.
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Wei, Guohua, Wubing Deng, Zhenchun Li, and Li-Yun Fu. "Sparsity-Enhanced Constrained Least-Squares Spectral Analysis with Greedy-FISTA." Remote Sensing 16, no. 18 (2024): 3486. http://dx.doi.org/10.3390/rs16183486.
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The utilization of the inversion-based algorithm for spectral decomposition using constrained least-squares spectral analysis (CLSSA) facilitates a time–frequency spectrum with higher temporal and frequency resolution. The conventional CLSSA algorithm is solved by optimizing an L2-norm regularized least-squares misfit function using Gaussian elimination, which suffers from intensive computational cost. Instead of solving an L2-norm regularized misfit function, we propose to use an L1-norm regularized objective function to enhance the sparsity of the resulting time–frequency spectra. Then, we utilize a faster, smarter, and greedier algorithm named greedy-FISTA to enhance the computational efficiency. Compared to the short-time Fourier transform, continuous wavelet transform, and the conventional CLSSA method, the sparsity-enhanced CLSSA with the greedy-FISTA is capable of achieving time–frequency spectra with higher resolution but with much less computational cost. The applicability of this sparsity-enhanced CLSSA method is demonstrated through synthetic and real data examples.
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Zhu, Hong, Qingping Wang, Ning Tai, Jingjian Huang, and Naichang Yuan. "Statistical Analysis of High-Resolution Coherent Monopulse Radar Sea Clutter." International Journal of Antennas and Propagation 2017 (2017): 1–28. http://dx.doi.org/10.1155/2017/7471918.
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A statistical analysis that properly characterizes sea clutter processes is indispensable both for optimum detection algorithm design and for performance prediction problems in maritime surveillance applications. In this paper, we present the statistical analysis of experimental sea clutter data collected by a high-resolution coherent monopulse radar. First, we present the amplitude statistical analyses for these clutter data. The results show that the K, Pareto, and CIG distributions can each provide good fits to the clutter data for three channels of monopulse radar. The analyses on the variations of the K distribution parameters with range suggest that the scale parameter is closely associated with the clutter powers and that the shape parameter is influenced by the sea state. Then, we focus on the correlation properties. The averaged results suggest that the temporal and spatial correlation properties are similar for the clutter of all three channels. Moreover, the clutter between the sum and difference channels is almost completely correlated in elevation and is lowly correlated in azimuth. Finally, we perform a spectral analysis, highlighting the temporal and spatial variabilities of Doppler spectra. It is found that the individual Doppler spectra in all three channels can be represented by Gaussian-shaped power spectral densities, and their centroid and width can be modeled as two separate stage linear functions of spectrum intensity.
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Puryear, Charles I., Oleg N. Portniaguine, Carlos M. Cobos, and John P. Castagna. "Constrained least-squares spectral analysis: Application to seismic data." GEOPHYSICS 77, no. 5 (2012): V143—V167. http://dx.doi.org/10.1190/geo2011-0210.1.
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An inversion-based algorithm for computing the time-frequency analysis of reflection seismograms using constrained least-squares spectral analysis is formulated and applied to modeled seismic waveforms and real seismic data. The Fourier series coefficients are computed as a function of time directly by inverting a basis of truncated sinusoidal kernels for a moving time window. The method resulted in spectra that have reduced window smearing for a given window length relative to the discrete Fourier transform irrespective of window shape, and a time-frequency analysis with a combination of time and frequency resolution that is superior to the short time Fourier transform and the continuous wavelet transform. The reduction in spectral smoothing enables better determination of the spectral characteristics of interfering reflections within a short window. The degree of resolution improvement relative to the short time Fourier transform increases as window length decreases. As compared with the continuous wavelet transform, the method has greatly improved temporal resolution, particularly at low frequencies.
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Small, Christopher, and Daniel Sousa. "Spectroscopic Phenological Characterization of Mangrove Communities." Remote Sensing 16, no. 15 (2024): 2796. http://dx.doi.org/10.3390/rs16152796.
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Spaceborne spectroscopic imaging offers the potential to improve our understanding of biodiversity and ecosystem services, particularly for challenging and rich environments like mangroves. Understanding the signals present in large volumes of high-dimensional spectroscopic observations of vegetation communities requires the characterization of seasonal phenology and response to environmental conditions. This analysis leverages both spectroscopic and phenological information to characterize vegetation communities in the Sundarban riverine mangrove forest of the Ganges–Brahmaputra delta. Parallel analyses of surface reflectance spectra from NASA’s EMIT imaging spectrometer and MODIS vegetation abundance time series (2000–2022) reveal the spectroscopic and phenological diversity of the Sundarban mangrove communities. A comparison of spectral and temporal feature spaces rendered with low-order principal components and 3D embeddings from Uniform Manifold Approximation and Projection (UMAP) reveals similar structures with multiple spectral and temporal endmembers and multiple internal amplitude continua for both EMIT reflectance and MODIS Enhanced Vegetation Index (EVI) phenology. The spectral and temporal feature spaces of the Sundarban represent independent observations sharing a common structure that is driven by the physical processes controlling tree canopy spectral properties and their temporal evolution. Spectral and phenological endmembers reside at the peripheries of the mangrove forest with multiple outward gradients in amplitude of reflectance and phenology within the forest. Longitudinal gradients of both phenology and reflectance amplitude coincide with LiDAR-derived gradients in tree canopy height and sub-canopy ground elevation, suggesting the influence of surface hydrology and sediment deposition. RGB composite maps of both linear (PC) and nonlinear (UMAP) 3D feature spaces reveal a strong contrast between the phenological and spectroscopic diversity of the eastern Sundarban and the less diverse western Sundarban.
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Peng, Zhao-Yang, Jia-Ming Chen, and Jirong Mao. "A Comparative Analysis of Two Peculiar Gamma-Ray Bursts: GRB 230307A and GRB 211211A." Astrophysical Journal 969, no. 1 (2024): 26. http://dx.doi.org/10.3847/1538-4357/ad45fc.
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Abstract GRB 211211A is a peculiar long gamma-ray burst (GRB) with very high brightness and short burst properties. Its full light curve consists of three emission episodes, i.e., a precursor, a main burst, and an extended emission. We find that a recently detected long-duration GRB 230307A also includes the three consistent emission episodes. Furthermore, the two bursts have similar redshifts, 0.076 and 0.065, respectively. We perform a detailed temporal and spectral analysis of the two GRBs to compare their temporal and spectral properties. Our analysis shows that the two bursts share great similarities for both the whole emission and the three corresponding emission phases, which are listed as follows: (1) they have near zero spectral lag; (2) they have very short minimum variability timescale (MVT); (3) they lie in the same region of in the MVT–T 90, Amati relation and hardness–T 90 planes; (4) the three phases are quasi-thermal spectra; (5) both the peak energy and the low-energy index track the flux; (6) the time-resolved spectra are much wider than those of the blackbody predicted by the model; (7) there are strong correlations between thermal flux and total flux and the correlation coefficients, and the slopes for the corresponding stages are very consistent; and (8) the photosphere emission properties are very consistent. Other investigations and observations suggest that the two GRBs indeed belong to a short burst with a compact star merger origin. Therefore, we think that GRB 230307A and GRB 211211A are rare and similar GRBs, and the photospheric radiation can interpret their radiation mechanisms.
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Kowalski, N., D. A. Depireux, and S. A. Shamma. "Analysis of dynamic spectra in ferret primary auditory cortex. II. Prediction of unit responses to arbitrary dynamic spectra." Journal of Neurophysiology 76, no. 5 (1996): 3524–34. http://dx.doi.org/10.1152/jn.1996.76.5.3524.
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1. Responses of single units and multiunit clusters were recorded in the ferret primary auditory cortex (AI) with the use of broadband complex dynamic spectra. Previous work has demonstrated that simpler spectra consisting of single moving ripples (i.e., sinusoidally modulated spectral profiles that travel at a constant velocity along the logarithmic frequency axis) could be used effectively to characterize the response fields and transfer functions of AI cells. 2. A complex dynamic spectral profile can be thought of as being the sum of moving ripple spectra. Such a decomposition can be computed from a two-dimensional spectrotemporal Fourier transform of the dynamic spectral profile with moving ripples as the basis function. 3. Therefore, if AI units were essentially linear, satisfying the superposition principle, then their responses to arbitrary dynamic spectra could be predicted from the responses to single moving ripples, i.e., from the units' response fields and transfer functions (spectral and temporal impulse response functions, respectively). 4. This conjecture was tested and confirmed with data from 293 combinations of moving ripples, involving complex spectra composed of up to 15 moving ripples of different ripple frequencies and velocities. For each case, response predictions based on the unit transfer functions were compared with measured responses. The correlation between predicted and measured responses was found to be consistently high (84% with rho > 0.6). 5. The distribution of response parameters suggests that AI cells may encode the profile of a dynamic spectrum by performing a multiscale spectrotemporal decomposition of the dynamic spectral profile in a largely linear manner.
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Sen, Kamal, Frédéric E. Theunissen, and Allison J. Doupe. "Feature Analysis of Natural Sounds in the Songbird Auditory Forebrain." Journal of Neurophysiology 86, no. 3 (2001): 1445–58. http://dx.doi.org/10.1152/jn.2001.86.3.1445.
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Although understanding the processing of natural sounds is an important goal in auditory neuroscience, relatively little is known about the neural coding of these sounds. Recently we demonstrated that the spectral temporal receptive field (STRF), a description of the stimulus-response function of auditory neurons, could be derived from responses to arbitrary ensembles of complex sounds including vocalizations. In this study, we use this method to investigate the auditory processing of natural sounds in the birdsong system. We obtain neural responses from several regions of the songbird auditory forebrain to a large ensemble of bird songs and use these data to calculate the STRFs, which are the best linear model of the spectral-temporal features of sound to which auditory neurons respond. We find that these neurons respond to a wide variety of features in songs ranging from simple tonal components to more complex spectral-temporal structures such as frequency sweeps and multi-peaked frequency stacks. We quantify spectral and temporal characteristics of these features by extracting several parameters from the STRFs. Moreover, we assess the linearity versus nonlinearity of encoding by quantifying the quality of the predictions of the neural responses to songs obtained using the STRFs. Our results reveal successively complex functional stages of song analysis by neurons in the auditory forebrain. When we map the properties of auditory forebrain neurons, as characterized by the STRF parameters, onto conventional anatomical subdivisions of the auditory forebrain, we find that although some properties are shared across different subregions, the distribution of several parameters is suggestive of hierarchical processing.
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Omran, A. K., M. A. Zaky, A. S. Hendy, and V. G. Pimenov. "An Efficient Hybrid Numerical Scheme for Nonlinear Multiterm Caputo Time and Riesz Space Fractional-Order Diffusion Equations with Delay." Journal of Function Spaces 2021 (December 6, 2021): 1–13. http://dx.doi.org/10.1155/2021/5922853.
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In this paper, we construct and analyze a linearized finite difference/Galerkin–Legendre spectral scheme for the nonlinear multiterm Caputo time fractional-order reaction-diffusion equation with time delay and Riesz space fractional derivatives. The temporal fractional orders in the considered model are taken as 0 < β 0 < β 1 < β 2 < ⋯ < β m < 1 . The problem is first approximated by the L 1 difference method on the temporal direction, and then, the Galerkin–Legendre spectral method is applied on the spatial discretization. Armed by an appropriate form of discrete fractional Grönwall inequalities, the stability and convergence of the fully discrete scheme are investigated by discrete energy estimates. We show that the proposed method is stable and has a convergent order of 2 − β m in time and an exponential rate of convergence in space. We finally provide some numerical experiments to show the efficacy of the theoretical results.
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Štych, Přemysl, Lucie Malíková, Jan Kříž, and Lukáš Holman. "Multi-temporal analysis of vegetation reflectance using MERIS data in the Czech Republic." Miscellanea Geographica 18, no. 2 (2014): 30–34. http://dx.doi.org/10.2478/mgrsd-2014-0015.
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Abstract Accurate high temporal resolution data is a very important source of information for understanding processes in the landscape. High temporal and spectral resolution data enable the monitoring of dynamic landscape processes. For this reason, since 2008 a receiving station for Metosat, NOAA and Envisat data has been installed at the Department of Applied Geoinformatics and Cartography, Faculty of Science, Charles University in Prague. The aim of this study is to analyse the spectral characteristics of vegetation using MERIS data in the Czech Republic. Spectral characteristics of vegetation were examined both by analysing changes in reflectivity as well as by utilising vegetation indices. Vegetation in forests and agricultural land was evaluated. The results present the spectral characteristics of selected associations of vegetation based on MERIS data and a discussion of the methods of multitemporal classification of land cover.
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Zhuo, R., L. Xu, J. Peng, and Y. Chen. "SPECTRAL UNMIXING ANALYSIS OF TIME SERIES LANDSAT 8 IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (May 2, 2018): 2609–14. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2609-2018.
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Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the “purified” pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of “purified” pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed “joint unmixing” approach provides more accurate endmember and abundance estimation results compared with “separate unmixing” approach.
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Tang, Bo, and Li Jiang. "Spectral Analysis for Temporal and Spatial Variability of AF Signal." Advanced Materials Research 459 (January 2012): 496–99. http://dx.doi.org/10.4028/scientific5/amr.459.496.
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Fostick, Leah, and Harvey Babkoff. "Auditory spectral versus spatial temporal order judgment: Threshold distribution analysis." Journal of Experimental Psychology: Human Perception and Performance 43, no. 5 (2017): 1002–12. http://dx.doi.org/10.1037/xhp0000359.
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Xie, Y., Y. P. Zhao, S. Jiang, M. Z. Mo, S. T. Yang, and Q. Wang. "Temporal and spectral analysis of capillary-discharge-pumped Ar8+ lasers." Journal of Russian Laser Research 31, no. 3 (2010): 276–80. http://dx.doi.org/10.1007/s10946-010-9146-2.
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Yin, Jiao, Jinli Cao, Siuly Siuly, and Hua Wang. "An Integrated MCI Detection Framework Based on Spectral-temporal Analysis." International Journal of Automation and Computing 16, no. 6 (2019): 786–99. http://dx.doi.org/10.1007/s11633-019-1197-4.
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Weber, S. M., A. Lindinger, M. Plewicki, C. Lupulescu, F. Vetter, and L. Wöste. "Temporal and spectral optimization course analysis of coherent control experiments." Chemical Physics 306, no. 1-3 (2004): 287–93. http://dx.doi.org/10.1016/j.chemphys.2004.07.045.
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Anandan, V. K., C. J. Pan, T. Rajalakshmi, and G. Ramachandra Reddy. "Multitaper spectral analysis of atmospheric radar signals." Annales Geophysicae 22, no. 11 (2004): 3995–4003. http://dx.doi.org/10.5194/angeo-22-3995-2004.
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Abstract. Multitaper spectral analysis using sinusoidal taper has been carried out on the backscattered signals received from the troposphere and lower stratosphere by the Gadanki Mesosphere-Stratosphere-Troposphere (MST) radar under various conditions of the signal-to-noise ratio. Comparison of study is made with sinusoidal taper of the order of three and single tapers of Hanning and rectangular tapers, to understand the relative merits of processing under the scheme. Power spectra plots show that echoes are better identified in the case of multitaper estimation, especially in the region of a weak signal-to-noise ratio. Further analysis is carried out to obtain three lower order moments from three estimation techniques. The results show that multitaper analysis gives a better signal-to-noise ratio or higher detectability. The spectral analysis through multitaper and single tapers is subjected to study of consistency in measurements. Results show that the multitaper estimate is better consistent in Doppler measurements compared to single taper estimates. Doppler width measurements with different approaches were studied and the results show that the estimation was better in the multitaper technique in terms of temporal resolution and estimation accuracy.
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Dadashova, K. Q., A. A. Mehdieva, and G. T. Agaeva. "SOME PECULIARITIES OF THE BRAIN BIOELECTRICAL ACTIVITY AT CHILDREN WITH ADHD." National Journal of Neurology 2, no. 02 (2012): 82–86. http://dx.doi.org/10.61788/njn.v2i12.11.
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The purpose of this study was to examine the spectral power of the EEG basic rhythms of children with ADHD (Attention Deficit Hyperactivity Disorder). The study involved 54 children of 7-9 years, who were divided into groups of children to cope successfully with the program (1) and having school difficulties (dysgraphia, dyslexia, attention deficit) (2). A comparative analysis of the power spectra in the delta, theta, alpha and beta bands. The spectral power of the alpha rhythm in the first group of children above the background with eyes closed in occipital-temporal areas of both hemispheres. The spectral power in the theta range with eyes closed in the left frontal and temporal regions were significantly higher in children of the second group as compared with the first. The decrease in spectral power at the main EEG frequencies in the left hemisphere of the second group of children points to the vulnerability of the left hemisphere under the influence of perinatal pathology factors, as the main criterion for assessing the maturity of brain activity in children is the formation of the alpha rhythm.
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Erb, Julia, Marcelo Armendariz, Federico De Martino, Rainer Goebel, Wim Vanduffel, and Elia Formisano. "Homology and Specificity of Natural Sound-Encoding in Human and Monkey Auditory Cortex." Cerebral Cortex 29, no. 9 (2018): 3636–50. http://dx.doi.org/10.1093/cercor/bhy243.
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Abstract Understanding homologies and differences in auditory cortical processing in human and nonhuman primates is an essential step in elucidating the neurobiology of speech and language. Using fMRI responses to natural sounds, we investigated the representation of multiple acoustic features in auditory cortex of awake macaques and humans. Comparative analyses revealed homologous large-scale topographies not only for frequency but also for temporal and spectral modulations. In both species, posterior regions preferably encoded relatively fast temporal and coarse spectral information, whereas anterior regions encoded slow temporal and fine spectral modulations. Conversely, we observed a striking interspecies difference in cortical sensitivity to temporal modulations: While decoding from macaque auditory cortex was most accurate at fast rates (> 30 Hz), humans had highest sensitivity to ~3 Hz, a relevant rate for speech analysis. These findings suggest that characteristic tuning of human auditory cortex to slow temporal modulations is unique and may have emerged as a critical step in the evolution of speech and language.
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Simões, Maurício dos Santos, Jansle Vieira Rocha, and Rubens Augusto Camargo Lamparelli. "Orbital spectral variables, growth analysis and sugarcane yield." Scientia Agricola 66, no. 4 (2009): 451–61. http://dx.doi.org/10.1590/s0103-90162009000400004.
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Temporal analysis of crop development in commercial fields requires tools for large area monitoring, such as remote sensing. This paper describes the temporal evolution of sugar cane biophysical parameters such as total biomass (BMT), yield (TSS), leaf area index (LAI), and number of plants per linear meter (NPM) correlated to Landsat data. During the 2000 and 2001 cropping seasons, a commercial sugarcane field in Araras, São Paulo state, Brazil, planted with the SP80-1842 sugarcane variety in the 4th and 5th cuts, was monitored using nine Landsat images. Spectral data were correlated with agronomic data, obtained simultaneously to the imagery acquisition. Two methodologies were used to collect spectral data from the images: four pixels (2 × 2) window and average of total pixels in the field. Linear and multiple regression analysis was used to study the spectral behavior of the plants and to correlate with agronomic variables (days after harvest-DAC, LAI, NPM, BMT and TSS). No difference was observed between the methodologies to collect spectral data. The best models to describe the spectral crop development in relation to DAC were the quadratic and cubic models. Ratio vegetation index and normalized difference vegetation index demonstrated correlation with DAC, band 3 (B3) was correlated with LAI, and NDVI was well correlated with TSS and BMT. The best fit curves to estimate TSS and BMT presented r² between 0.68 and 0.97, suggesting good potential in using orbital spectral data to monitor sugarcane fields.
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Citrin, D. S. "Fibonacci signals with timing jitter." Mathematics in Engineering 5, no. 4 (2023): 1–13. http://dx.doi.org/10.3934/mine.2023076.
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<abstract><p>The power spectral density of a signal comprised of a sequence of Dirac $ \delta $-functions at successive times determined by a Fibonacci sequence is the temporal analog of the well known structure factor for a Fibonacci chain. Such a signal is quasi-periodic and, under suitable choice of parameters, is the temporal analog of a one-dimensional quasicrystal. While the effects of disorder in the spatial case of Fibonacci chains has been studied numerically, having an analytically tractable stochastic model is needed both for the spatial and temporal cases to be able to study these effects as model parameters are varied. Here, we consider the effects of errors in where the $ \delta $-functions defining the signal in the temporal case occur, i.e., timing jitter. In this work, we present an analytically tractable theory of how timing jitter affects the power spectral density of Fibonacci signals.</p></abstract>
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Fernandes, Francisco C. R., Maurício J. A. Bolzan, Reinaldo R. Rosa, et al. "Semi-harmonic and intermittent solar decimetric spikes." Proceedings of the International Astronomical Union 5, S264 (2009): 81–83. http://dx.doi.org/10.1017/s1743921309992420.
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AbstractWe present the analysis of the narrowband solar radio spike emissions observed by the Brazilian Solar Spectroscope (BSS) on 24 June, 1999, at 16:53:55–16:56:48 UT. The data were recorded with temporal resolution of 50 ms and frequency resolution of 5 MHz. The dynamic spectra of clusters of spikes were recorded in 100 channels in the 1.2-1.7 GHz frequency band. The groups of radio spikes observed clearly show spectral semi-harmonic structures and an intermittent temporal patter. The observational parameters were determined from the dynamic spectra analysis. The wavelet analysis technique able us to determine the temporal cadence for the clusters. The frequency ratio between two clusters of spikes recorded at same time were inferred. The preliminary results show average cadence of clusters of spikes occurrence of about 32 seconds and a semi-harmonic average frequency ratio of the order of 1:1.2.
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Kević, Veronika, Ivan Racetin, and Andrija Krtalić. "Temporal Analysis of Multispectral Satellite Data for the Purpose of Urbanization Monitoring." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W13-2025 (July 11, 2025): 165–70. https://doi.org/10.5194/isprs-archives-xlviii-4-w13-2025-165-2025.
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Abstract. Monitoring the urbanization process and early detection of illegal construction should enable meaningful urban planning and the protection of natural and cultural features of the community. There is a major problem of illegal construction in the Republic of Croatia. In 2023 alone, according to a report by the State Inspectorate of the Republic of Croatia, a total of 4,774 inspections were carried out on the territory of the Republic of Croatia, and 1,089 inspection procedures were initiated due to violations of construction regulations. The aim of this paper was to examine and determine the possibilities of applying remote sensing methods in the early detection of areas under construction or other types of devastation. The evaluation of the quality and usability of the results refers to reliability of the detection of areas under construction using the images of the Sentinel-2 and PlanetScope satellite systems. In order to detect those areas, ten spectral indices were for two reference dates one in 2017 and 2021 (nine indices for Sentinel-2 and one for Planetscope). The results of this research include analysis of spectral indices for detection and identification of land parcels that exhibit land cover changes from natural to human construction. The city of Solin and Podstrana municipality (near Split, Croatia), with its wider surroundings, were selected for the research area. The best results were achieved with the difference of NDVI spectral indices calculated using the spectral channels of the Sentinel-2 and PlanetScope satellite systems. Achieved results, showed also that the spatial resolution of the used spectral bands (3 m PlanetScope and 10 m Sentinel-2) did not have a major impact on the accuracy of detection for this specific application.
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Kacic, Patrick, and Claudia Kuenzer. "Forest Biodiversity Monitoring Based on Remotely Sensed Spectral Diversity—A Review." Remote Sensing 14, no. 21 (2022): 5363. http://dx.doi.org/10.3390/rs14215363.
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Forests are essential for global environmental well-being because of their rich provision of ecosystem services and regulating factors. Global forests are under increasing pressure from climate change, resource extraction, and anthropologically-driven disturbances. The results are dramatic losses of habitats accompanied with the reduction of species diversity. There is the urgent need for forest biodiversity monitoring comprising analysis on α, β, and γ scale to identify hotspots of biodiversity. Remote sensing enables large-scale monitoring at multiple spatial and temporal resolutions. Concepts of remotely sensed spectral diversity have been identified as promising methodologies for the consistent and multi-temporal analysis of forest biodiversity. This review provides a first time focus on the three spectral diversity concepts “vegetation indices”, “spectral information content”, and “spectral species” for forest biodiversity monitoring based on airborne and spaceborne remote sensing. In addition, the reviewed articles are analyzed regarding the spatiotemporal distribution, remote sensing sensors, temporal scales and thematic foci. We identify multispectral sensors as primary data source which underlines the focus on optical diversity as a proxy for forest biodiversity. Moreover, there is a general conceptual focus on the analysis of spectral information content. In recent years, the spectral species concept has raised attention and has been applied to Sentinel-2 and MODIS data for the analysis from local spectral species to global spectral communities. Novel remote sensing processing capacities and the provision of complementary remote sensing data sets offer great potentials for large-scale biodiversity monitoring in the future.
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Zabelinsky, I. E., N. G. Bikova, P. V. Kozlov, V. Yu Levashov, and G. Ya Gerasimov. "RADIATIVE CHARACTERISTICS OF SHOCK HEATED OXYGEN." Journal of Applied Spectroscopy 89, no. 1 (2022): 64–68. http://dx.doi.org/10.47612/0514-7506-2022-89-1-64-68.
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The emission spectra of oxygen behind the front of a strong shock wave have been studied in the shock wave velocity ranges of 5.7—7.4 and 8.1—10.0 km/s at pressures before the wave front of 1.0 and 0.25 Torr. Time-integrated sweeps of radiation in a wide spectral range of 200—675 nm as well as temporal oscillograms
 of oxygen radiation have been obtained. An analysis of the obtained panoramic spectra shows that at low velocities of the shock wave, the system of Schumann—Runge molecular bands dominates in the emission spectrum. An increase in the shock wave velocity leads to the appearance of intense atomic lines in the emission spectrum. The peculiarities of temporal oscillograms for the most typical spectral lines, such as radiation of molecular oxygen at a wavelength of 213 nm (Schumann—Runge system) and radiation of atomic oxygen at wavelengths of 394 and 645 nm, are highlighted.
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Abdelkawy, M. A., and S. A. Alyami. "A Spectral Collocation Technique for Riesz Fractional Chen-Lee-Liu Equation." Journal of Function Spaces 2021 (April 12, 2021): 1–9. http://dx.doi.org/10.1155/2021/5567970.
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This paper discusses the study of optical solitons that are modeled by Riesz fractional Chen-Lee-Liu model, one of the versions of the famous nonlinear Schrödinger equation. This model is solved by the assistance of consecutive spectral collocation technique with two independent approaches. The first is the approach of the spatial variable, while the other is the approach of the temporal variable. It is concluded that the method of the current paper is far more efficient and credible for the proposed problem. Numerical results illustrate the performance efficiency of the algorithm. The results also point out that the scheme can lead to spectral accuracy of the studied model.
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Tsai, Shih-Chiao, Jenn-Shyong Chen, Yen-Hsyang Chu, Ching-Lun Su, and Jui-Hsiang Chen. "High-range resolution spectral analysis of precipitation through range imaging of the Chung-Li VHF radar." Atmospheric Measurement Techniques 11, no. 1 (2018): 581–92. http://dx.doi.org/10.5194/amt-11-581-2018.
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Abstract. Multi-frequency range imaging (RIM) has been operated in the Chung-Li very high-frequency (VHF) radar, located on the campus of National Central University, Taiwan, since 2008. RIM processes the echo signals with a group of closely spaced transmitting frequencies through appropriate inversion methods to obtain high-resolution distribution of echo power in the range direction. This is beneficial to the investigation of the small-scale structure embedded in dynamic atmosphere. Five transmitting frequencies were employed in the radar experiment for observation of the precipitating atmosphere during the period between 21 and 23 August 2013. Using the Capon and Fourier methods, the radar echoes were synthesized to retrieve the temporal signals at a smaller range step than the original range resolution defined by the pulse width, and such retrieved temporal signals were then processed in the Doppler frequency domain to identify the atmosphere and precipitation echoes. An analysis called conditional averaging was further executed for echo power, Doppler velocity, and spectral width to verify the potential capabilities of the retrieval processing in resolving small-scale precipitation and atmosphere structures. Point-by-point correction of range delay combined with compensation of range-weighting function effect has been performed during the retrieval of temporal signals to improve the continuity of power spectra at gate boundaries, making the small-scale structures in the power spectra more natural and reasonable. We examined stratiform and convective precipitation and demonstrated their different structured characteristics by means of the Capon-processed results. The new element in this study is the implementation of RIM on spectral analysis, especially for precipitation echoes.
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Nofuentes, Gustavo, Christian A. Gueymard, José A. Caballero, Guilherme Marques-Neves, and Jorge Aguilera. "Experimental Evaluation of a Spectral Index to Characterize Temporal Variations in the Direct Normal Irradiance Spectrum." Applied Sciences 11, no. 3 (2021): 897. http://dx.doi.org/10.3390/app11030897.
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A simple index is desirable to assess the effects on both flat-plate and concentrating photovoltaics of natural changes in the solar spectrum. Some studies have suggested that the relationship between the Average Photon Energy (APE) and the shape of individual global tilted irradiance, global horizontal irradiance, or direct normal irradiance (DNI) spectra is bijective and can therefore be used as a single number to unequivocally replace a complete spectral distribution. This paper reevaluates these studies with a modified methodology to assess whether a one-to-one relationship really exists between APE and spectral DNI. A 12-month dataset collected in Jaén (Spain) using a sun-tracking spectroradiometer provides the necessary spectral DNI data between 350 and 1050 nm. After quality control and filtering, 78,772 valid spectra were analyzed. The methodology is based on a statistical analysis of the spectral distributions binned in 0.02-eV APE intervals, from 1.74 to 1.90 eV. For each interval, both the standard deviation and coefficient of variation (CV) are determined across all 50-nm bands into which the 350–1050-nm waveband is divided. CV stays below 3.5% within the 450–900-nm interval but rises up to 13% outside of it. It is concluded that APE may be approximately assumed to uniquely characterize the DNI spectrum distribution for Jaén (and presumably for locations with similar climates) only over the limited 450–900-nm waveband.
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Kowalski, N., D. A. Depireux, and S. A. Shamma. "Analysis of dynamic spectra in ferret primary auditory cortex. I. Characteristics of single-unit responses to moving ripple spectra." Journal of Neurophysiology 76, no. 5 (1996): 3503–23. http://dx.doi.org/10.1152/jn.1996.76.5.3503.
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1. Auditory stimuli referred to as moving ripples are used to characterize the responses of both single and multiple units in the ferret primary auditory cortex. Moving ripples are broadband complex sounds with a sinusoidal spectral profile that drift along the logarithmic frequency axis at a constant velocity. 2. Neuronal responses to moving ripples are locked to the phase of the ripple, i.e., they exhibit the same periodicity as that of the moving ripple profile. Neural responses are characterized as a function of ripple velocity (temporal property) and ripple frequency (spectral property). Transfer functions describing the response to these temporal and spectral modulations are constructed. Temporal transfer functions are inverse Fourier transformed to obtain impulse response functions that reflect the cell's temporal characteristics. Ripple transfer functions are inverse Fourier transformed to obtain the response field, a measure analogous to the cell's response area. These operations assume linearity in the cell's response to moving ripples. 3. Transfer functions and other response functions are shown to be fairly independent on the overall level or depth of modulation of the ripple stimuli. Only downward moving ripples were used in this study. 4. The temporal and ripple transfer functions are found to be separable, in that their shapes remain unchanged for different test parameters. Thus ripple transfer functions and response fields remain statistically similar in shape (to within an overall scale factor) regardless of the ripple velocity or whether stationary or moving ripples are used in the measurement. The same stability in shape holds for the temporal transfer functions and the impulse response functions measured with different ripple frequencies. Separability implies that the combined spectrotemporal transfer function of a cell can be written as the product of a purely ripple and a purely temporal transfer functions, and thus that the neuron can be computationally modeled as processing spectral and temporal information in two separate and successive stages. 5. The ripple parameters that characterize cortical cells are distributed somewhat evenly, with the characteristic ripple frequencies ranging from 0.2 to > 2 cycles/octave and the characteristic angular frequency typically ranging from 2 to 20 Hz. 6. Many responses exhibit periodicities in the spectral envelope of the stimulus. These periodicities are of two types. Slow rebounds, not found in the spectral envelope, and with a period of approximately 150 ms, appear with various strengths in approximately 30% of the cells. Fast regular firings with interspike intervals of approximately 10 ms are much less common and appear to correspond to interactions between the component tones that make up a ripple.