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Relevant bibliographies by topics / Spectral and temporal analysis

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Academic literature on the topic 'Spectral and temporal analysis'

Author: Grafiati

Published: 4 June 2025

Last updated: 15 July 2025

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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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Dissertations / Theses on the topic "Spectral and temporal analysis"

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Everett, M. S. "The temporal and spectral characteristics of recorded music." Thesis, Coventry University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382924.

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Mello, Marcio Pupin. "Spectral-temporal and Bayesian methods for agricultural remote sensing data analysis." Instituto Nacional de Pesquisas Espaciais (INPE), 2013. http://urlib.net/sid.inpe.br/mtc-m19/2013/09.17.18.58.

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Informações agrícolas confiáveis tem se tornado cada vez mais importantes para os tomadores de decisões. Especialmente quando são obtidas em tempo hábil, essas informações são altamente relevantes para o planejamento estratégico do país. Apesar de o sensoriamento remoto mostrar-se promissor para aplicações em mapeamento agrícola, com potencial de melhorar as estatísticas agrícolas oficiais, esse potencial não tem sido amplamente explorado. Existem poucos exemplos bem sucedidos do uso operacional do sensoriamento remoto para mapeamento sistemático de culturas agrícolas e, para garantir resultados precisos, eles são fortemente baseados em interpretação visual de imagens. De fato, apesar dos substanciais avanços em análise de dados de sensoriamento remoto, novas técnicas para automatizar a análise de dados em sensoriamento remoto com aplicações agrícolas são desejáveis, especialmente no propósito de manter a consistência e a precisão dos resultados. Neste contexto, existe uma demanda crescente pelo desenvolvimento e implementação de métodos automatizados de análise de dados de sensoriamento remoto com aplicações em agricultura. Assim, o principal objetivo desta tese é propor o desenvolvimento e a implementação de métodos para automatizar a análise de dados de sensoriamento remoto em aplicações agrícolas, com foco na consistência e precisão dos resultados. Este documento foi escrito como uma coleção de dois artigos, cada um com foco nos seguintes pontos: (i) análise multitemporal, multiespectral e multisensor, permitindo a descrição das variações espectrais de alvos agrícolas ao longo do tempo; e (ii) inteligência artificial na modelagem de fenômenos usando dados de sensoriamento remoto e informações complementares de maneira integrada. Dois estudos de caso referentes ao mapeamento da colheita da cana em São Paulo e ao mapeamento da soja no Mato Grosso foram usados para testar as metodologias batizadas de STARS e BayNeRD, respectivamente. Os resultados dos testes confirmaram que ambos os métodos propostos foram capazes de automatizar processos de análises de dados de sensoriamento remoto com aplicações agrícolas, com consistência e precisão.<br>Reliable agricultural statistics has become increasingly important to decision makers. Especially when timely obtained, agricultural information is highly relevant to the strategic planning of the country. Although remote sensing shows to be of great potential for agricultural mapping applications, with the benefit of further improving official agricultural statistics, its potential has not been fully explored. There are very few successful examples of operational remote sensing application for systematic mapping of agricultural crops, and they are strongly supported by visual image interpretation to allow accurate results. Indeed, despite the substantial advances in remote sensing data analysis, techniques to automate remote sensing data analysis focusing on agricultural mapping applications are highly valuable but have to maintain consistency and accuracy. In this context, there continues to be a demand for development and implementation of computer aided methods to automate the processes of analyzing remote sensing datasets for agriculture applications. Thus, the main objective of this thesis is to propose implementation of computer aided methodologies to automate, maintaining consistency and accuracy, processes of remote sensing data analyses focused on agricultural thematic mapping applications. This thesis was written as a collection of two papers related to a core theme, each addressing the following main points: (i) multitemporal, multispectral and multisensor image analysis that allow the description of spectral changes of agricultural targets over time; and (ii) artificial intelligence in modeling phenomena using remote sensing and ancillary data. Study cases of sugarcane harvest in São Paulo and soybean mapping in Mato Grosso were used to test the proposed methods named STARS and BayNeRD, respectively. The two methods developed and tested confirm that remotely sensed (and ancillary) data analysis can be automated with computer aided methods to model a range of cropland phenomena for agriculture applications, maintaining consistency and accuracy.

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Kuster, Markus. "Combined spectral and temporal analysis of a Her X-1 turn-on." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=971486271.

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Malfrait, Paul. "Temporal spectral unmixing for rapid detection of radiological events by gamma ray spectrometry." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG055.

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Cette thèse vise à améliorer les algorithmes de démélange de spectres gamma afin de pouvoir accélérer la détection d'anomalie et l'estimation des contributions des radionucléides contenus dans les filtres aérosols analysés par l'Institut de Radioprotection et de Sûreté Nucléaire. Pour ce faire nous avons développé un algorithme de démélange de spectre qui analyse conjointement plusieurs mesures successives d'un même échantillon.Cet algorithme a ensuite été amélioré afin de pouvoir mener l'analyse en temps réel pendant que la mesure du spectre gamma est réalisée. Divers outils ont dû être développés en même temps que cet algorithme pour permettre d'estimer précisémment les activités des radionnucléides, notamment la calibration des signatures spectrales utilisées lors du démélange.Les résultats de ces études sont présentés dans la thèse à la fois sur des spectres simulés et sur des spectres réels issus des analyses de routine du laboratoire. La détection d'une contamination de ¹²³I à 2 Bq dans un échantillon au bout de 2 minutesde mesure illustre bien l'accélération permise par les développement de cette thèse. En effet, cette détection n'aurait pas été possible avec les outils utilisés en routine<br>The aim of this thesis is to improve spectral unmixing algorithms in gamma ray spectrometry in order to speed up anomaly detection and the estimation of radionuclide contributions in aerosol filter samples analyzed by the French Institute of Radiation Protection and Nuclear Safety. To this end, we have developed an unmixing algorithm that performs joint analysis of several successive measurements of the same sample. This algorithm has been improved to enable online analysis while the gamma-ray spectrum measurement is measured. Various tools had to be developed at the same time as this algorithm to enable radionuclide activities to be estimated accurately, including calibration of the spectral signatures used during the unmixing process.The results of these studies are presented in the thesis both on simulated spectra and on real spectra from the laboratory's routine analyses. The detection of a contamination of ¹²³I at 2 Bq in a sample after 2 minutes of measurement illustrates the acceleration made possible by the developments made during this thesis. Indeed, this detection would not have been possible with the tools used routinely

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Garges, David Casimir. "Early Forest Fire Detection via Principal Component Analysis of Spectral and Temporal Smoke Signature." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1456.

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The goal of this study is to develop a smoke detecting algorithm using digital image processing techniques on multi-spectral (visible & infrared) video. By utilizing principal component analysis (PCA) followed by spatial filtering of principal component images the location of smoke can be accurately identified over a period of exposure time with a given frame capture rate. This result can be further analyzed with consideration of wind factor and fire detection range to determine if a fire is present within a scene. Infrared spectral data is shown to contribute little information concerning the smoke signature. Moreover, finalized processing techniques are focused on the blue spectral band as it is furthest away from the infrared spectral bands and because it experimentally yields the largest footprint in the processed principal component images in comparison to other spectral bands. A frame rate of .5 images/sec (1 image every 2 seconds) is determined to be the maximum such that temporal variance of smoke can be captured. The study also shows eigenvectors corresponding to the principal components that best represent smoke and are valuable indications of smoke temporal signature. Raw video data is taken through rigorous pre-processing schemes to align frames from respective spectral band both spatially and temporally. A multi-paradigm numerical computing program, MATLAB, is used to match the field of view across five spectral bands: Red, Green, Blue, Long-Wave Infrared, and Mid-Wave Infrared. Extracted frames are aligned temporally from key frames throughout the data capture. This alignment allows for more accurate digital processing for smoke signature. v Clustering analysis on RGB and HSV value systems reveal that color alone is not helpful to segment smoke. The feature values of trees and other false positives are shown to be too closely related to features of smoke for in solely one instance in time. A temporal principal component transform on the blue spectral band eliminates static false positives and emphasizes the temporal variance of moving smoke in images with higher order. A threshold adjustment is applied to a blurred blue principal component of non-unity principal component order and smoke results can be finalized using median filtering. These same processing techniques are applied to difference images as a more simple and traditional technique for identifying temporal variance and results are compared.

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Jennings, Amanda R. "On mechanisms for the analysis of spectral and temporal envelope shape in the human auditory system." Thesis, University of Newcastle Upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.413390.

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Kriss, Alissa Brynn. "The Role of Environmental, Temporal, and Spatial Scale on the Heterogeneity of Fusarium Head Blight of Wheat." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1320932280.

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Guo, Ziyuan. "Objective Audio Quality Assessment Based on Spectro-Temporal Modulation Analysis." Thesis, KTH, Ljud- och bildbehandling, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-91847.

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Objective audio quality assessment is an interdisciplinary research area that incorporates audiology and machine learning. Although much work has been made on the machine learning aspect, the audiology aspect also deserves investigation. This thesis proposes a non-intrusive audio quality assessment algorithm, which is based on an auditory model that simulates human auditory system. The auditory model is based on spectro-temporal modulation analysis of spectrogram, which has been proven to be effective in predicting the neural activities of human auditory cortex. The performance of an implementation of the algorithm shows the effectiveness of the spectro-temporal modulation analysis in audio quality assessment.

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Zhang, Chi, and 张驰. "Ultrafast temporal spectroscopy based on parametric mixing time-lens." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/200358.

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With the increased requirement on the ultrafast measurement technology, how to resolve the spectral dynamics has the top priority on the research list, since spectrum is an essential carrier for most of the physical or chemical phenomena. According to the Nyquist-Shannon sampling theorem, if a function 𝑥(𝑡) contains no frequencies higher than 𝐵 Hz, it is completely determined by giving its ordinates at a series of points spaced 1/(2𝐵) seconds apart. Since most of the conventional optical spectrum analyzers (OSAs) are operated with the sampling rate (or frame rate) of 5 Hz, it results in the resolvable bandwidth of the spectrum dynamic is less than 2.5 Hz. With the development of the space-time duality, the analogy transforms the conventional spatial dimension into the time axis, and the well-known spatial models inspire us in performing their counterparts in the time domain. As one of the most powerful tools in achieving ultrafast time axis information, time-lens plays a more and more important role in the single-pixel imaging system. By fully analyzing the diploma of the previous optical spectrum resolving mechanisms, in this thesis, for the first time, we raised up the concept the parametric spectrotemporal analyzer (PASTA), which is based on the time-lens focusing mechanism. Here the spectrum resolving frame rate is increased to 100 MHz, then the observable spectrum dynamic bandwidth could be 50 MHz, which is sufficient for most of the ultrafast phenomena. In the PASTA system, the time-lenses are implemented with the fiber optical parametric amplifier (FOPA) based parametric mixer, which provides higher conversion efficiency and repetition rate. On the other hand, the dispersion based dispersive Fourier transformation (DFT) technology generates the swept-pump for the FOPA, as well as the temporal dispersion medium. This research in this thesis is a fundamental study on the newly PASTA system, from its origin and the theoretical background, to the implementation techniques and operation performances. From its implementation, its principles are strongly related with the combination of the dispersion and the Kerr nonlinear effects, especially the swept-pump FOPA in the time-lens part. The DFT technique, in generating the fast swept-source, has also find its applications in the ultrafast serial time-encoded amplified microscopy (STEAM) and swept-source optical coherence tomography (SS-OCT) systems. Finally, the single-lens PASTA prototype is capable of resolving 5-nm wavelength range with 0.03-nm resolution under 100-MHz frame rate. Moreover, besides the singlelens PASTA, the telescope/wide-angle configurations have also been investigated experimentally to achieve the spectrum zoom in/out ratio as high as 17 times, here we have obtained the sharpest resolution of 5 pm (<1 GHz) with the telescope configuration, and the widest observation range of 9 nm with the wide-angle configuration. My research efforts presented in this thesis mainly leverage the ultrafast characteristics of the time-lens system, from theory to implementation, and achieve the real-time optical spectrum analysis – the PASTA system. PASTA is not only essential in observing some non-repetitive ultrafast phenomena, but also provides a potential solution for the frequency to time transformation in some ultrafast bio-medical imaging systems.<br>published_or_final_version<br>Electrical and Electronic Engineering<br>Doctoral<br>Doctor of Philosophy

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Orstavik, Odd-Halvdan Sakse. "Analysis of chaotic multi-variate time-series from spatio-temporal dynamical systems." Thesis, University College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314071.

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Books on the topic "Spectral and temporal analysis"

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Priestley, M. B. Spectral analysis and time series. 5th ed. Academic Press, 1987.

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Koopmans, Lambert Herman. The spectral analysis of time series. 2nd ed. Academic Press, 1995.

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United States. National Aeronautics and Space Administration., ed. X-ray spectral and temporal studies of the ultra-compact system X1916-05: Final report (8/15/96 - 2/14/98), grant NAG5-3298. National Aeronautics and Space Administration, 1998.

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United States. National Aeronautics and Space Administration., ed. X-ray spectral and temporal studies of the ultra-compact system X1916-05: Final report (8/15/96 - 2/14/98), grant NAG5-3298. National Aeronautics and Space Administration, 1998.

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Grindlay, Jonathan E. X-ray spectral and temporal studies of the ultra-compact system X1916-05: Final report (8/15/96 - 2/14/98), grant NAG5-3298. National Aeronautics and Space Administration, 1998.

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United States. National Aeronautics and Space Administration., ed. X-ray spectral and temporal studies of the ultra-compact system X1916-05: Final report (8/15/96 - 2/14/98), grant NAG5-3298. National Aeronautics and Space Administration, 1998.

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Castani, Francis, ed. Spectral Analysis. ISTE, 2006. http://dx.doi.org/10.1002/9780470612194.

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Cecconi, Jaures, ed. Spectral Analysis. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-10955-3.

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service), SpringerLink (Online, ed. Spectral Analysis. Springer-Verlag Berlin Heidelberg, 2011.

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Castanié, Francis, ed. Digital Spectral Analysis. John Wiley & Sons, Inc, 2011. http://dx.doi.org/10.1002/9781118601877.

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Book chapters on the topic "Spectral and temporal analysis"

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Tohyama, Mikio. "Temporal and Spectral Characteristics of Discrete Sequence." In Waveform Analysis of Sound. Springer Japan, 2014. http://dx.doi.org/10.1007/978-4-431-54424-1_3.

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Tohyama, Mikio. "Temporal and Spectral Enhancement by Sound Path." In Waveform Analysis of Sound. Springer Japan, 2014. http://dx.doi.org/10.1007/978-4-431-54424-1_4.

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Bernardis, Elena, Ender Konukoglu, Yangming Ou, Dimitris N. Metaxas, Benoit Desjardins, and Kilian M. Pohl. "Temporal Shape Analysis via the Spectral Signature." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33418-4_7.

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Abel, H. H., D. Klüßendorf, E. Koralewski, R. Krause, and R. Droh. "Spectral Analysis of Heart Rate During Different States of Activity." In Temporal Variations of the Cardiovascular System. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-662-02748-6_5.

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Luo, Qiasi. "Enhance Multi-bit Spectral Analysis on Hiding in Temporal Dimension." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12510-2_2.

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Cury, Claire, Marco Lorenzi, David Cash, et al. "Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease." In Spectral and Shape Analysis in Medical Imaging. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-51237-2_6.

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Toscani, Matteo, and Anna Metzger. "A Database of Vibratory Signals from Free Haptic Exploration of Natural Material Textures and Perceptual Judgments (ViPer): Analysis of Spectral Statistics." In Haptics: Science, Technology, Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06249-0_36.

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AbstractWe recorded vibratory patterns elicited by free haptic exploration of a large set of natural textures with a steel tool tip. Vision and audio signals during the exploration were excluded. After the exploration of each sample, participants provided judgments about its perceptual attributes and material category. We found that vibratory signals can be approximated by a single parameter in the temporal frequency domain, in a similar way as we can describe the spatial frequency spectrum of natural images. This parameter varies systematically between material categories and correlates with human perceptual judgements. It provides an estimate of the spectral composition of the power spectra which is highly correlated with the differential activity of the Rapidly Adapting (RA) and Pacinian Corpuscle (PC) afferents.

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Rodriguez, Luis Garcia, Jonas Konrad, Dominik Drees, and Benjamin Risse. "S-ROPE: Spectral Frame Representation of Periodic Events." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-92460-6_19.

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Abstract In this paper we introduce a novel event surface representation designed for encoding temporal information of dynamic vision sensors (DVS) into a multi-channel frame format. Different representations have been proposed to extract features from event streams. Among these representations, time surfaces have become a popular choice due to their ability to provide a flattened view of event data over a specified time interval. Despite their widespread adaption, these methods suffer from loss of crucial temporal information. This disadvantage is particularly apparent in DVS applications with repetitive, high-frequency intensity changes, as these signals result in continuously elevated event rates and would therefore benefit from efficient, yet information preserving representations. Moreover, integrating this information into state-of-the-art vision-based machine learning models remains challenging. To address these limitations, we propose Spectral frame Representation of Periodic Events (S-ROPE) which leverages information from frequency domain analysis through the application of the Fourier transformation and arranges the resulting frequency, amplitude and phase into spatially consistent frames. By transforming event streams from the temporal domain to the frequency domain, we demonstrate improved preservation of temporal dynamics, especially for objects displaying high frequency oscillations. We evaluate S-ROPE frames on custom and several publicly available datasets and demonstrate the applicability for three distinct use cases: visualisation, compression and machine learning-based image processing. For the latter, we show that S-ROPE proves useful for object detection in a scenery with high frequency events.

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Delville, J., Z. Chahine, and J. P. Bonnet. "Experimental Study of an Incompressible, Plane Mixing Layer by Temporal and Spectral Analysis." In Advances in Turbulence. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83045-7_49.

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Lam, Toby H. W., Tony W. H. Ao Ieong, and Raymond S. T. Lee. "Silhouette Spatio-temporal Spectrum (SStS) for Gait-Based Human Recognition." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11552499_35.

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Conference papers on the topic "Spectral and temporal analysis"

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Eladlani, Mohamed Alae-Eddine, Larbi Boubchir, and Khadidja Benallou. "Temporal-Spectral Analysis for Speaker Identification and Authentication in Emotional Speech." In 2024 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT). IEEE, 2024. https://doi.org/10.1109/bdcat63179.2024.00061.

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Brajović, Miloš, Isidora Stanković, Miloš Daković, and Ljubiša Stanković. "Spectral Analysis of Temporal Signals on DAGs Using Joint Time-Vertex Fourier Transform." In 2025 29th International Conference on Information Technology (IT). IEEE, 2025. https://doi.org/10.1109/it64745.2025.10930286.

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Tang, Chengchuang, Liying Yang, Gang Cao, Jingtao Du, and Qian Zhang. "ST-GCN: EEG Emotion Recognition via Spectral Graph and Temporal Analysis with Graph Convolutional Networks." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822712.

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Li, Lun, Saiyang Liu, Chen Liu, Yitian Gong, Chi Zhang, and Xinliang Zhang. "Temporal aperture synthesis system for high-resolution spectrum analysis." In 2024 IEEE Opto-Electronics and Communications Conference (OECC). IEEE, 2024. https://doi.org/10.1109/oecc54135.2024.10975352.

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Heritage, J. P., A. M. Weiner, and R. N. Thurston. "Picosecond Pulse Shaping and Complex Spectral Analysis." In International Conference on Ultrafast Phenomena. Optica Publishing Group, 1986. http://dx.doi.org/10.1364/up.1986.tua1.

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Ultrashort light pulses may be tailored to arbitrary shapes using spectral masking in a grating pulse compressor. We use this technique to perform novel double-slit temporal interference measurements of the optical phase. We observe the reshapping of the optical phase spectrum due to stimulated Raman scattering.

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Antonacci, Julian, Eneas N. Morel, Jorge Torga, Ricardo Duchowicz, and Gustavo F. Arenas. "Spectral sensor resolution measurement improvements by temporal analysis." In 2017 XVII Workshop on Information Processing and Control (RPIC). IEEE, 2017. http://dx.doi.org/10.23919/rpic.2017.8214341.

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Zou, Rui, Wenye Wang, and Huaiyu Dai. "Temporal and Spectral Analysis of Spectrum Hole Distributions in an LTE Cell." In GLOBECOM 2021 - 2021 IEEE Global Communications Conference. IEEE, 2021. http://dx.doi.org/10.1109/globecom46510.2021.9685339.

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Su, Hongjun, Yehua Sheng, and Yongning Wen. "Data mining based on spectral and spatial features for hyperspectral classification." In International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, edited by Yaolin Liu and Xinming Tang. SPIE, 2009. http://dx.doi.org/10.1117/12.837304.

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Asimopolos, Laurentiu, and Agata Monica Pestina. "Temporal, spectral and wavelet analysis applied for geomagnetic data." In Proceedings of the 9th SEGJ International Symposium. Society of Exploration Geophysicists of Japan, 2009. http://dx.doi.org/10.1190/segj092009-001.37.

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Wang, Xihong, Stephen A. Zahorian, and Stefan Auberg. "Analysis of speech segments using variable spectral/temporal resolution." In 4th International Conference on Spoken Language Processing (ICSLP 1996). ISCA, 1996. http://dx.doi.org/10.21437/icslp.1996-315.

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Reports on the topic "Spectral and temporal analysis"

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Hall, Joseph W. Auditory Spectro-Temporal Pattern Analysis. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada253037.

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Hall, Joseph W., Grose III, Hatch John, Wilson Deborah, Dev Adam, and Madhu. Auditory Spectro-Temporal Pattern Analysis. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada309836.

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Hall, Joseph W. Auditory Spectro-Temporal Pattern Analysis. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada264691.

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Hall, Joseph W. Auditory Spectro-Temporal Pattern Analysis. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada273554.

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Hall, Joseph W. Auditory Spectro-Temporal Pattern Analysis. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada218416.

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Gu, Zu-Han. Temporal and Spectral Coherence From Rough Surface Scattering. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada442610.

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Kissick, William, ed. The Temporal and Spectral Characteristics of Ultrawideband Signals. Institute for Telecommunication Sciences, 2001. https://doi.org/10.70220/dvlxbqjd.

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Arnoldus, Henk F., and Thomas F. George. Spectral and Temporal Distribution of Phase-Conjugated Fluorescent Photons. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada230504.

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Shokair, Isaac R. Detection of embedded radiation sources using temporal variation of gamma spectral data. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1030395.

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Georgiou, Tryphon T. High Resolution Spectral Analysis. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada534538.

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