Gotowe bibliografie tematyczne / Non-stationary tide

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Gotowa bibliografia na temat „Non-stationary tide”

Autor: Grafiati
Data publikacji: 18 listopada 2022
Data aktualizacji: 21 grudnia 2022

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Artykuły w czasopismach na temat "Non-stationary tide"

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Manson, A. H., C. E. Meek, T. Chshyolkova, X. Xu, T. Aso, J. R. Drummond, C. M. Hall i in. "Arctic tidal characteristics at Eureka (80° N, 86° W) and Svalbard (78° N, 16° E) for 2006/07: seasonal and longitudinal variations, migrating and non-migrating tides". Annales Geophysicae 27, nr 3 (9.03.2009): 1153–73. http://dx.doi.org/10.5194/angeo-27-1153-2009.

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Abstract. Operation of a Meteor Radar at Eureka, Ellesmere Island (80° N, 86° W) began in February 2006. The first 12 months of wind data (82–97 km) are combined with winds from the Adventdalen, Svalbard Island (78° N, 16° E) Meteor Radar to provide the first contemporaneous longitudinally spaced observations of mean winds, tides and planetary waves at such high Arctic latitudes. Unique polar information on diurnal non-migrating tides (NMT) is provided, as well as complementary information to that existing for the Antarctic on the semidiurnal NMT. Zonal and meridional monthly mean winds differed significantly between Canada and Norway, indicating the influence of stationary planetary waves (SPW) in the Arctic mesopause region. Both diurnal (D) and semi-diurnal (SD) winds also demonstrated significantly different magnitudes at Eureka and Svalbard. Typically the D tide was larger at Eureka and the SD tide was larger at Svalbard. Tidal amplitudes in the Arctic were also generally larger than expected from extrapolation of high mid-latitude data. For example time-sequences from ~90 km showed D wind oscillations at Eureka of 30 m/s in February–March, and four day bursts of SD winds at Svalbard reached 40 m/s in June 2006. Fitting of wave numbers for the migrating and non-migrating tides (MT, NMT) successfully determines dominant tides for each month and height. For the diurnal tide, NMT with s=0, +2 (westward) dominate in non-summer months, while for the semi-diurnal tide NMT with s=+1, +3 occur most often during equinoctial or early summer months. These wave numbers are consistent with stationary planetary wave (SPW)-tidal interactions. Assessment of the global topographic forcing and atmospheric propagation of the SPW (S=1, 2) suggests these winter waves of the Northern Hemisphere are associated with the 78–80° N diurnal NMT, but that the SPW of the Southern Hemisphere winter have little influence on the summer Arctic tidal fields. In contrast the large SPW and NMT of the Arctic winter may be associated, consistent with Antarctic observations, with the observed occurrence of the semidiurnal NMT in the Antarctic summer.
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Carrere, Loren, Brian K. Arbic, Brian Dushaw, Gary Egbert, Svetlana Erofeeva, Florent Lyard, Richard D. Ray i in. "Accuracy assessment of global internal-tide models using satellite altimetry". Ocean Science 17, nr 1 (19.01.2021): 147–80. http://dx.doi.org/10.5194/os-17-147-2021.

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Abstract. Altimeter measurements are corrected for several geophysical parameters in order to access ocean signals of interest, like mesoscale or sub-mesoscale variability. The ocean tide is one of the most critical corrections due to the amplitude of the tidal elevations and to the aliasing phenomena of high-frequency signals into the lower-frequency band, but the internal-tide signatures at the ocean surface are not yet corrected globally. Internal tides can have a signature of several centimeters at the surface with wavelengths of about 50–250 km for the first mode and even smaller scales for higher-order modes. The goals of the upcoming Surface Water Ocean Topography (SWOT) mission and other high-resolution ocean measurements make the correction of these small-scale signals a challenge, as the correction of all tidal variability becomes mandatory to access accurate measurements of other oceanic signals. In this context, several scientific teams are working on the development of new internal-tide models, taking advantage of the very long altimeter time series now available, which represent an unprecedented and valuable global ocean database. The internal-tide models presented here focus on the coherent internal-tide signal and they are of three types: empirical models based upon analysis of existing altimeter missions, an assimilative model and a three-dimensional hydrodynamic model. A detailed comparison and validation of these internal-tide models is proposed using existing satellite altimeter databases. The analysis focuses on the four main tidal constituents: M2, K1, O1 and S2. The validation process is based on a statistical analysis of multi-mission altimetry including Jason-2 and Cryosphere Satellite-2 data. The results show a significant altimeter variance reduction when using internal-tide corrections in all ocean regions where internal tides are generating or propagating. A complementary spectral analysis also gives some estimation of the performance of each model as a function of wavelength and some insight into the residual non-stationary part of internal tides in the different regions of interest. This work led to the implementation of a new internal-tide correction (ZARON'one) in the next geophysical data records version-F (GDR-F) standards.
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D’Arcy, Eleanor, Jonathan A. Tawn i Dafni E. Sifnioti. "Accounting for Climate Change in Extreme Sea Level Estimation". Water 14, nr 19 (21.09.2022): 2956. http://dx.doi.org/10.3390/w14192956.

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Extreme sea level estimates are fundamental for mitigating coastal flooding as they provide insight for defence engineering. As the global climate changes, rising sea levels combined with increases in storm intensity and frequency pose an increasing risk to coastline communities. We present a new method for estimating extreme sea levels that accounts for the effects of climate change on extreme events that are not accounted for by mean sea level trends. We follow a joint probabilities methodology, considering skew surge and peak tides as the only components of sea levels. We model extreme skew surges using a non-stationary generalised Pareto distribution (GPD) with covariates accounting for climate change, seasonality and skew surge–peak tide interaction. We develop methods to efficiently test for extreme skew surge trends across different coastlines and seasons. We illustrate our methods using data from four UK tide gauges and estimate sea level return levels when accounting for these long-term trends.
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Das, Uma, William E. Ward, Chen Jeih Pan i Sanat Kumar Das. "Migrating and non-migrating tides observed in the stratosphere from FORMOSAT-3/COSMIC temperature retrievals". Annales Geophysicae 38, nr 2 (31.03.2020): 421–35. http://dx.doi.org/10.5194/angeo-38-421-2020.

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Abstract. Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere and Climate (FORMOSAT-3/COSMIC) temperature data during October 2009–December 2010 are analysed for tides in the middle atmosphere from ∼10 to 50 km. COSMIC is a set of six micro-satellites in near-Sun-synchronous orbits with 30∘ orbital separations that provides good phase space sampling of tides. Short-term tidal variability is deduced by considering ±10 d data together. The migrating diurnal (DW1) tide is found to peak over the Equator at 30 km. It maximises and slightly shifts poleward during winters. Over middle and high latitudes, DW1 and the non-migrating diurnal tides with wavenumber 0 (DS0) and wavenumber 2 (DW2) are intermittent in nature. Numerical experiments in the current study show that these could be a result of aliasing as they are found to occur at times of a steep rise or fall in the mean temperature, particularly during the sudden stratospheric warming (SSW) of 2010. Further, the stationary planetary wave component of wavenumber 1 (SPW1) is found to be of very large amplitudes in the Northern Hemisphere, reaching 18 K at 30 km over 65∘ N. By using data from COSMIC over shorter durations, it is shown that aliasing between stationary planetary wave and non-migrating tides is reduced and thus results in the large amplitudes of the former. This study clearly indicates that non-linear interactions are not a very important source for the generation of non-migrating tides in the middle- and high-latitude winter stratosphere. There is also a modulation of SPW1 by a ∼60 d oscillation in the high latitudes, which was not seen earlier.
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Falanga, Mariarosaria, Enza De Lauro, Simona Petrosino i Salvatore De Martino. "Interaction between seismicity and deformation on different time scales in volcanic areas: Campi Flegrei and Stromboli". Advances in Geosciences 52 (5.12.2019): 1–8. http://dx.doi.org/10.5194/adgeo-52-1-2019.

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Abstract. We study oscillations recorded at Stromboli and Campi Flegrei by different sensors: seismometers, strainmeters and tiltmeters. We examine both the high-frequency (>0.5 Hz) portion of the spectrum and very long period signals up to tidal scales. In this context, seismicity and deformation are investigated on different time scales (from minutes to days/years) in order to identify the basic elements of their interaction, whose understanding should provide new insights on the predictive models. In this work, the strict relation of tides and volcanic processes is shown. At Stromboli, indeed the transition from the stationary phase to the non-stationary phase seems to have a tidal precursor that is related to the duration of the crisis. The subsequent volcanic activity is interpreted as the response of the volcano to restore the equilibrium condition. The moveout from equilibrium produces, first, variations in the standard statistics of explosions, then leads to effusive stage and to a pressure drop in the shallow feeding system. That process induces the nucleation of a gas bubble and the excitation of low frequencies. Campi Flegrei seismicity shows a correlation between the diurnal solar solid tide and the energy released by the long period signals, indicating that the whole mechanism is modulated on a tidal scale. In other words, in the case of Stromboli, a departure from the equilibrium state is marked by solid tide variations in a certain frequency band. On the other hand, at Campi Flegrei diurnal to annual solid tides modulate an increase of volcanic activity.
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Zoppetti, F. A., H. Folonier, A. M. Leiva i C. Beaugé. "Creep tide model for the three-body problem". Astronomy & Astrophysics 651 (lipiec 2021): A49. http://dx.doi.org/10.1051/0004-6361/202140957.

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We present a tidal model for treating the rotational evolution in the general three-body problem with arbitrary viscosities, in which all the masses are considered to be extended and all the tidal interactions between pairs are taken into account. Based on the creep tide theory, we present a set of differential equations that describes the rotational evolution of each body, in a formalism that is easily extensible to the N tidally interacting body problem. We apply our model to the case of a circumbinary planet and use a Kepler-38 like binary system as a working example. We find that, in this low planetary eccentricity case, the most likely final stationary rotation state is the 1:1 spin–orbit resonance, considering an arbitrary planetary viscosity inside the estimated range for the Solar System planets. The timescales for reaching the equilibrium state are expected to be approximately millions of years for stiff bodies but can be longer than the age of the system for planets with a large gaseous component. We derive analytical expressions for the mean rotational stationary state, based on high-order power series of the ratio of the semimajor axes a1∕a2 and low-order expansions of the eccentricities. These are found to very accurately reproduce the mean behaviour of the low-eccentric numerical integrations for arbitrary planetary relaxation factors, and up to a1∕a2 ~ 0.4. Our analytical model is used to predict the stationary rotation of the Kepler circumbinary planets and we find that most of them are probably rotating in a subsynchronous state, although the synchrony shift is much less important than our previous estimations. We present a comparison of our results with those obtained with the Constant Time Lag and find that, as opposed to the assumptions in our previous works, the cross torques have a non-negligible net secular contribution, and must be taken into account when computing the tides over each body in an N-extended-body system from an arbitrary reference frame. These torques are naturally taken into account in the creep theory. In addition to this, the latter formalism considers more realistic rheology that proved to reduce to the Constant Time Lag model in the gaseous limit and also allows several additional relevant physical phenomena to be studied.
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Lühr, H., i C. Manoj. "The complete spectrum of the equatorial electrojet related to solar tides: CHAMP observations". Annales Geophysicae 31, nr 8 (5.08.2013): 1315–31. http://dx.doi.org/10.5194/angeo-31-1315-2013.

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Abstract. Based on 10 yr of magnetic field measurements by the CHAMP satellite we draw a detailed picture of the equatorial electrojet (EEJ) tidal variations. For the first time the complete EEJ spectrum related to average solar tides has been compiled. A large fraction of the resulting spectrum is related to the switch on/off of the EEJ between day and night. This effect has carefully been considered when interpreting the results. As expected, largest amplitudes are caused by the migrating tides representing the mean diurnal variation. Higher harmonics of the daily variations show a 1/f fall-off in amplitude. Such a spectrum is required to represent the vanishing of the EEJ current at night. The migrating tidal signal exhibits a distinct annual variation with large amplitudes during December solstice and equinox seasons but a depression by a factor of 1.7 around June–July. A rich spectrum of non-migrating tidal effects is deduced. Most prominent is the four-peaked longitudinal pattern around August. Almost 90% of the structure can be attributed to the diurnal eastward-propagating tide DE3. In addition the westward-propagating DW5 is contributing to wave-4. The second-largest non-migrating tide is the semi-diurnal SW4 around December solstice. It causes a wave-2 feature in satellite observations. The three-peaked longitudinal pattern, often quoted as typical for the December season, is significantly weaker. During the months around May–June a prominent wave-1 feature appears. To first order it represents a stationary planetary wave SPW1 which causes an intensification of the EEJ at western longitudes beyond 60° W and a weakening over Africa/India. In addition, a prominent ter-diurnal non-migrating tide TW4 causes the EEJ to peak later, at hours past 14:00 local time in the western sector. A particularly interesting non-migrating tide is the semi-diurnal SW3. It causes largest EEJ amplitudes from October through December. This tidal component shows a strong dependence on solar flux level with increasing amplitudes towards solar maximum. We are not aware of any previous studies mentioning this behaviour of SW3. The main focus of this study is to present the observed EEJ spectrum and its relation to tidal driving. For several of the identified spectral components we cannot offer convincing explanations for the generation mechanisms.
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Manson, A. H., C. E. Meek, X. Xu, T. Aso, J. R. Drummond, C. M. Hall, W. K. Hocking, M. Tsutsumi i W. E. Ward. "Characteristics of Arctic tides at CANDAC-PEARL (80° N, 86° W) and Svalbard (78° N, 16° E) for 2006–2009: radar observations and comparisons with the model CMAM-DAS". Annales Geophysicae 29, nr 10 (31.10.2011): 1939–54. http://dx.doi.org/10.5194/angeo-29-1939-2011.

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Abstract. Operation of a Meteor Radar (MWR) at Eureka, Ellesmere Island (80° N, 86° W) began in February 2006: this is the location of the Polar Environmental and Atmospheric Research Laboratory (PEARL), operated by the "Canadian Network for the Detection of Atmospheric Change" (CANDAC). The first 36 months of tidal wind data (82–97 km) are here combined with contemporaneous tides from the Meteor Radar (MWR) at Adventdalen, Svalbard (78° N, 16° E), to provide the first significant evidence for interannual variability (IAV) of the High Arctic's diurnal and semidiurnal migrating (MT) and non-migrating tides (NMT). The three-year monthly means for both diurnal (DT) and semi-diurnal (SDT) winds demonstrate significantly different amplitudes and phases at Eureka and Svalbard. Typically the summer-maximizing DT is much larger (~24 m s−1 at 97 km) at Eureka, while the Svalbard tide (5–24 m s−1 at 97 km)) is almost linear (north-south) rather than circular. Interannual variations are smallest in the summer and autumn months. The High Arctic SDT has maxima centred on August/September, followed in size by the winter features; and is much larger at Svalbard (24 m s−1 at 97 km, versus 14–18 m s−1 in central Canada). Depending on the location, the IAV are largest in spring/winter (Eureka) and summer/autumn (Svalbard). Fitting of wave-numbers for the migrating and non-migrating tides (MT, NMT) determines dominant tides for each month and height. Existence of NMT is consistent with nonlinear interactions between migrating tides and (quasi) stationary planetary wave (SPW) S=1 (SPW1). For the diurnal oscillation, NMT s=0 for the east-west (EW) wind component dominates (largest tide) in the late autumn and winter (November–February); and s=+2 is frequently seen in the north-south (NS) wind component for the same months. The semi-diurnal oscillation's NMT s=+1 dominates from March to June/July. There are patches of s=+3 and +1, in the late fall-winter. These wave numbers are also consistent with SPW1-MT interactions. Comparisons for 2007 of the observed DT and SDT at 78–80° N, with those within the Canadian Middle Atmosphere Model Data Assimilation System CMAM-DAS, are a major feature of this paper. The diurnal tides for the two locations have important similarities as observed and modeled, with seasonal maxima in the mesosphere from April to October, and similar phases with long/evanescent wavelengths. However, differences are also significant: observed Eureka amplitudes are generally larger than the model; and at Svalbard the modeled tide is classically circular, rather than anomalous. For the semi-diurnal tide, the amplitudes and phases differ markedly between Eureka and Svalbard for both MWR-radar data and CMAM-DAS data. The seasonal variations from observed and modeled archives also differ at each location. Tidal NMT-amplitudes and wave-numbers for the model differ substantially from observations.
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Wahl, T., J. Jensen i T. Frank. "On analysing sea level rise in the German Bight since 1844". Natural Hazards and Earth System Sciences 10, nr 2 (1.02.2010): 171–79. http://dx.doi.org/10.5194/nhess-10-171-2010.

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Abstract. In this paper, a methodology to analyse observed sea level rise (SLR) in the German Bight, the shallow south-eastern part of the North Sea, is presented. The paper focuses on the description of the methods used to generate and analyse mean sea level (MSL) time series. Parametric fitting approaches as well as non-parametric data adaptive filters, such as Singular System Analysis (SSA) are applied. For padding non-stationary sea level time series, an advanced approach named Monte-Carlo autoregressive padding (MCAP) is introduced. This approach allows the specification of uncertainties of the behaviour of smoothed time series near the boundaries. As an example, the paper includes the results from analysing the sea level records of the Cuxhaven tide gauge and the Heligoland tide gauge, both located in the south-eastern North Sea. For comparison, the results from analysing a worldwide sea level reconstruction are also presented. The results for the North Sea point to a weak negative acceleration of SLR since 1844 with a strong positive acceleration at the end of the 19th century, to a period of almost no SLR around the 1970s with subsequent positive acceleration and to high recent rates.
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Onohara, Amelia Naomi, Inez Staciarini Batista i Paulo Prado Batista. "Wavenumber-4 structures observed in the low-latitude ionosphere during low and high solar activity periods using FORMOSAT/COSMIC observations". Annales Geophysicae 36, nr 2 (21.03.2018): 459–71. http://dx.doi.org/10.5194/angeo-36-459-2018.

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Abstract. The main purpose of this study is to investigate the four-peak structure observed in the low-latitude equatorial ionosphere by the FORMOSAT/COSMIC satellites. Longitudinal distributions of NmF2 (the density of the F layer peak) and hmF2 (ionospheric F2-layer peak height) averages, obtained around September equinox periods from 2007 to 2015, were submitted to a bi-spectral Fourier analysis in order to obtain the amplitudes and phases of the main waves. The four-peak structure in the equatorial and low-latitude ionosphere was present in both low and high solar activity periods. This kind of structure possibly has tropospheric origins related to the tidal waves propagating from below that modulate the E-region dynamo, mainly the eastward non-migrating diurnal tide with wavenumber 3 (DE3, E for eastward). This wave when combined with the migrating diurnal tide (DW1, W for westward) presents a wavenumber-4 (wave-4) structure under a synoptic view. Electron densities observed during 2008 and 2013 September equinoxes revealed that the wave-4 structures became more prominent around or above the F-region altitude peak (∼ 300–350 km). The four-peak structure remains up to higher ionosphere altitudes (∼ 800 km). Spectral analysis showed DE3 and SPW4 (stationary planetary wave with wavenumber 4) signatures at these altitudes. We found that a combination of DE3 and SPW4 with migrating tides is able to reproduce the wave-4 pattern in most of the ionospheric parameters. For the first time a study using wave variations in ionospheric observations for different altitude intervals and solar cycle was done. The conclusion is that the wave-4 structure observed at high altitudes in ionosphere is related to effects of the E-region dynamo combined with transport effects in the F region.
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Rozprawy doktorskie na temat "Non-stationary tide"

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凌仕卿 i Shiqing Ling. "Stationary and non-stationary time series models with conditional heteroscedasticity". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B31236005.

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Ling, Shiqing. "Stationary and non-stationary time series models with conditional heteroscedasticity /". Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18611953.

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Xu, Mengyuan Tracy. "Filtering non-stationary time series by time deformation". Ann Arbor, Mich. : ProQuest, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3309151.

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Thesis (Ph.D. in Statistical Science)--S.M.U.
Title from PDF title page (viewed Mar. 16, 2009). Source: Dissertation Abstracts International, Volume: 69-04, Section: B, page: 2402. Advisers: Wayne A. Woodward; Henry L. Gray. Includes bibliographical references.
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Campbell, N. C. "Statistical methods for non-stationary time series analysis". Thesis, University of Cambridge, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597266.

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This dissertation is concerned with Bayesian methods for non-stationary time series analysis. Most of the algorithms developed use Markov chain Monte Carlo (MCMC) methods as the means of sampling from the required posteriors. A stochastic version of the Expectation Maximisation (EM) algorithm, the Expectation Sample (ES) algorithm is developed. The performance of this algorithm is compared with EM and other stochastic EM algorithms for parameter estimation of locally stationary time series. The ES algorithm is shown to overcome some of the well documented limitations of the EM algorithm. Non-stationary time series are commonly modelled by segmenting them into a number of independent frames that can be considered stationary. An algorithm is developed whereby these individuals segments can be considered to be dependent on each other. This algorithm is used for the task of noise reduction of a long audio signal and it is shown that the new algorithm gives improved results compared to existing techniques. The time-varying Autoregressive (TVAR) model is introduced as a non-stationary time series model. Basis functions are used to model the TVAR coefficients and an MCMC algorithm developed to perform subset selection on the set of chosen basis functions. Results show that this algorithm is capable of reducing the number of basis functions used to model each TVAR coefficient. The subset selection algorithm is extended to deal with the problem of unknown TVAR model order. Two MCMC algorithms are developed; a reversible jump algorithm and a combined subset selection algorithm. An application to noise reduction of audio signals is considered. The techniques developed previously are extended to account for the fact that the signal is now observed in noise. The algorithm is demonstrated using real audio with added white noise.
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Chen, Hao. "Real time model adaptation for non-linear and non-stationary systems". Thesis, University of Reading, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.630445.

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This thesis studies the modelling for the non-linear and non-stationary systems. In a highly non-stationary environment, not only the model coefficients but also the model structure should be adapted with time. A number of novel on-line modeling approaches are proposed in this thesis. The proposed approaches are validated using several benchmark signal processing applications including time series prediction, noise cancellation and channel equalization. First, a novel tunable radial basis function network is proposed. in which the number of nodes (or the model size) of the network is fixed and a new structured node is used to replace the worst performing node whenever the current network does not fit the input data. Two schemes are proposed to optimize t.he structure of the new node: a powerful version based on the quantum particle swarm optimization algorithm and a fast version based on the "gradient search" approach. Secondly, a new online multiple modelling approach is proposed for nonstationary systems. The proposed multimodel approach is based on two level structures of linear sub-models. The advantage of the proposed method is that it is very fast, making it particularly suitable for real time applications. Finally a new adaptive channel equalizer is developed based on minimum biterror- rate. A key issue in the minimum bit-error-rate equalizer is how the probability density function of an associated signed decision variable can be estimated on-line. In the proposed equalizer, a novel online probability density function based on Gaussian mixture model is derived, which has significant better performance than existing approaches.
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Muševič, Sašo. "Non-stationary sinusoidal analysis". Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/123809.

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Muchos tipos de señales que encontramos a diario pertenecen a la categoría de sinusoides no estacionarias. Una gran parte de esas señales son sonidos que presentan una gran variedad de características: acústicos/electrónicos, sonidos instrumentales harmónicos/impulsivos, habla/canto, y la mezcla de todos ellos que podemos encontrar en la música. Durante décadas la comunidad científica ha estudiado y analizado ese tipo de señales. El motivo principal es la gran utilidad de los avances científicos en una gran variedad de áreas, desde aplicaciones médicas, financiera y ópticas, a procesado de radares o sonar, y también a análisis de sistemas. La estimación precisa de los parámetros de sinusoides no estacionarias es una de las tareas más comunes en procesado digital de señales, y por lo tanto un elemento fundamental e indispensable para una gran variedad de aplicaciones. Las transformaciones de tiempo y frecuencia clásicas son solamente apropiadas para señales con variación lenta de amplitud y frecuencia. Esta suposición no suele cumplirse en la práctica, lo que conlleva una degradación de calidad y la aparición de artefactos. Además, la resolución temporal y frecuencial no se puede incrementar arbitrariamente debido al conocido principio de incertidumbre de Heisenberg. \\ El principal objetivo de esta tesis es revisar y mejorar los métodos existentes para el análisis de sinusoides no estacionarias, y también proponer nuevas estrategias y aproximaciones. Esta disertación contribuye sustancialmente a los análisis sinusoidales existentes: a) realiza una evaluación crítica del estado del arte y describe con gran detalle los métodos de análisis existentes, b) aporta mejoras sustanciales a algunos de los métodos existentes más prometedores, c) propone varias aproximaciones nuevas para el análisis de los modelos sinusoidales existentes i d) propone un modelo sinusoidal muy general y flexible con un algoritmo de análisis directo y rápido.
Many types of everyday signals fall into the non-stationary sinusoids category. A large family of such signals represent audio, including acoustic/electronic, pitched/transient instrument sounds, human speech/singing voice, and a mixture of all: music. Analysis of such signals has been in the focus of the research community for decades. The main reason for such intense focus is the wide applicability of the research achievements to medical, financial and optical applications, as well as radar/sonar signal processing and system analysis. Accurate estimation of sinusoidal parameters is one of the most common digital signal processing tasks and thus represents an indispensable building block of a wide variety of applications. Classic time-frequency transformations are appropriate only for signals with slowly varying amplitude and frequency content - an assumption often violated in practice. In such cases, reduced readability and the presence of artefacts represent a significant problem. Time and frequency resolu
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Wong, W. K. "Some contributions to multivariate stationary non-linear time series". Thesis, University of Manchester, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540596.

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Guillaumin, Arthur P. "Quasi-likelihood inference for modulated non-stationary time series". Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10044853/.

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In this thesis we propose a new class of non-stationary time series models and a quasi-likelihood inference method that is computationally efficient and consistent for that class of processes. A standard class of non-stationary processes is that of locally-stationary processes, where a smooth time-varying spectral representation extends the spectral representation of stationary time series. This allows us to apply stationary estimation methods when analysing slowly-varying non-stationary processes. However, stationary inference methods may lead to large biases for more rapidly-varying non-stationary processes. We present a class of such processes based on the framework of modulated processes. A modulated process is formed by pointwise multiplying a stationary process, called the latent process, by a sequence, called the modulation sequence. Our interest lies in estimating a parametric model for the latent stationary process from observing the modulated process in parallel with the modulation sequence. Very often exact likelihood is not computationally viable when analysing large time series datasets. The Whittle likelihood is a stan- dard quasi-likelihood for stationary time series. Our inference method adapts this function by specifying the expected periodogram of the modulated process for a given parameter vector of the latent time series model, and then fits this quantity to the sample periodogram. We prove that this approach conserves the computational efficiency and convergence rate of the Whittle likelihood under increasing sample size. Finally, our real-data application is concerned with the study of ocean surface currents. We analyse bivariate non-stationary velocities obtained from instruments following the ocean surface currents, and infer key physical quantities from this dataset. Our simulations show the benefit of our modelling and estimation method.
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Nguyen, Yen Thi Hong. "Time-frequency distributions : approaches for incomplete non-stationary signals". Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/19681/.

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There are many sources of waveforms or signals existing around us. They can be natural phenomena such as sound, light and invisible like electromagnetic fields, voltage, etc. Getting an insight into these waveforms helps explain the mysteries surrounding our world and the signal spectral analysis (i.e. the Fourier transform) is one of the most significant approaches to analyze a signal. Nevertheless, Fourier analysis cannot provide a time-dependent spectrum description for spectrum-varying signals-non-stationary signal. In these cases, time-frequency distribu- tions are employed instead of the traditional Fourier transform. There have been a variety of methods proposed to obtain the time-frequency representations (TFRs) such as the spectrogram or the Wigner-Ville distribution. The time-frequency distributions (TFDs), indeed, offer us a better signal interpretation in a two-dimensional time-frequency plane, which the Fourier transform fails to give. Nevertheless, in the case of incomplete data, the time-frequency displays are obscured by artifacts, and become highly noisy. Therefore, signal time-frequency features are hardly extracted, and cannot be used for further data processing. In this thesis, we propose two methods to deal with compressed observations. The first one applies compressive sensing with a novel chirp dictionary. This method assumes any windowed signal can be approximated by a sum of chirps, and then performs sparse reconstruction from windowed data in the time domain. A few improvements in computational complexity are also included. In the second method, fixed kernel as well as adaptive optimal kernels are used. This work is also based on the assumption that any windowed signal can be approximately represented by a sum of chirps. Since any chirp's auto-terms only occupy a certain area in the ambiguity domain, the kernel can be designed in a way to remove the other regions where auto-terms do not reside. In this manner, not only cross-terms but also missing samples’ artifact are mitigated significantly. The two proposed approaches bring about a better performance in the time-frequency signature estimations of the signals, which are sim- ulated with both synthetic and real signals. Notice that in this thesis, we only consider the non-stationary signals with frequency changing slowly with time. It is because the signals with rapidly varying frequency are not sparse in time-frequency domain and then the compressive sensing techniques or sparse reconstructions could not be applied. Also, the data with random missing samples are obtained by randomly choosing the samples’ positions and replacing these samples with zeros.
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Brat, Guillaume Philippe. "A (max,+) algebra for non-stationary and non-deterministic periodic discrete event systems /". Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Książki na temat "Non-stationary tide"

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Priestly, M. B. Non-linear and non-stationary time series. London: Academic Press, 1988.

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Segal, Mordechai. Time delay estimation in stationary and non-stationary environments. Woods Hole, Mass: Woods Hole Oceanographic Institution, 1988.

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Priestley, M. B. Non-linear and non-stationary time series analysis. London: Academic Press, 1988.

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Hunter, John, Simon P. Burke i Alessandra Canepa. Multivariate Modelling of Non-Stationary Economic Time Series. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-31303-4.

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Wong, W. K. Some contributions to multivariate stationary non-linear time series. Manchester: UMIST, 1993.

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Moukadem, Ali, Djaffar Ould Abdeslam i Alain Dieterlen. Time-Frequency Domain for Segmentation and Classification of Non-Stationary Signals. Hoboken, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118908686.

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Qian, Ying. Optimal hedging strategy re-visited: Acknowledging the existence of non-stationary economic time series. [Washington, DC]: World Bank, International Economics Dept., International Trade Division, 1994.

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Bergstrom, A. R. The estimation of parameters in non-stationary higher order continuous time dynamic models. [Colchester]: Department of Economics, University of Essex, 1985.

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Priestly, M. B. Non-linear and non-stationary time series analysis. Academic, 1988.

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Priestly. Non-linear and Stationary Time Series Analysis. Elsevier, 1991.

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Części książek na temat "Non-stationary tide"

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Cowpertwait, Paul S. P., i Andrew V. Metcalfe. "Non-stationary Models". W Introductory Time Series with R, 137–57. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-88698-5_7.

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Widiputra, Harya, Russel Pears i Nikola Kasabov. "Dynamic Learning of Multiple Time Series in a Nonstationary Environment". W Learning in Non-Stationary Environments, 303–47. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-8020-5_12.

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Hunter, John, Simon P. Burke i Alessandra Canepa. "Multivariate Time Series". W Multivariate Modelling of Non-Stationary Economic Time Series, 21–75. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-31303-4_2.

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Sahu, B. K. "Non-Stationary Univariate Time Series Models". W Time Series Modelling in Earth Sciences, 153–73. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003211280-3.

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Ramachandra Rao, A., Khaled H. Hamed i Huey-Long Chen. "Segmentation of Non-Stationary Time Series". W Nonstationarities in Hydrologic and Environmental Time Series, 213–52. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-010-0117-5_7.

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Mills, Terence C. "Non-stationary Time Series: Differencing and ARIMA Modelling". W Time Series Econometrics, 41–57. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137525338_3.

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Hunter, John, Simon P. Burke i Alessandra Canepa. "The Structural Analysis of Time Series". W Multivariate Modelling of Non-Stationary Economic Time Series, 383–439. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-31303-4_9.

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Hunter, John, Simon P. Burke i Alessandra Canepa. "Introduction". W Multivariate Modelling of Non-Stationary Economic Time Series, 1–19. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-31303-4_1.

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Hunter, John, Simon P. Burke i Alessandra Canepa. "Cointegration". W Multivariate Modelling of Non-Stationary Economic Time Series, 77–144. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-31303-4_3.

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Hunter, John, Simon P. Burke i Alessandra Canepa. "Testing for Cointegration: Standard and Non-Standard Conditions". W Multivariate Modelling of Non-Stationary Economic Time Series, 145–204. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-31303-4_4.

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Streszczenia konferencji na temat "Non-stationary tide"

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Guan, Heshan, Shuliang Zou, Mengya Liu i Tieli Wang. "Clustering univariate time series into stationary and non-stationary". W 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2010. http://dx.doi.org/10.1109/fskd.2010.5569228.

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HUTT, A., i F. KRUGGEL. "FIXED POINT ANALYSIS: DYNAMICS OF NON-STATIONARY SPATIOTEMPORAL SIGNALS". W Space-Time Chaos: Characterization, Control and Synchronization. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812811660_0003.

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Kalinggo, Bonnie Alexandra, i Zulkarnain. "Time Series Forecasting for Non-stationary Data". W APCORISE 2020: 3rd Asia Pacific Conference on Research in Industrial and Systems Engineering 2020. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3400934.3400952.

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Pukhova, Valentina M., Taras V. Kustov i Gabriele Ferrini. "Time-frequency analysis of non-stationary signals". W 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). IEEE, 2018. http://dx.doi.org/10.1109/eiconrus.2018.8317292.

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Dorken, E., i S. H. Nawab. "Time-frequency analysis of non-stationary harmonic sounds". W Proceedings of ICASSP '93. IEEE, 1993. http://dx.doi.org/10.1109/icassp.1993.319483.

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Kuchansky, Alexander, Andrii Biloshchytskyi, Yurii Andrashko, Svitlana Biloshchytska, Tetyana Honcharenko i Volodymyr Nikolenko. "Fractal Time Series Analysis in Non-Stationary Environment". W 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T). IEEE, 2019. http://dx.doi.org/10.1109/picst47496.2019.9061554.

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Hasanov, Aydin, i Sayyar Abdullayev. "Integrated analysis technology of non-stationary time series". W 2012 IV International Conference "Problems of Cybernetics and Informatics" (PCI). IEEE, 2012. http://dx.doi.org/10.1109/icpci.2012.6486292.

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Barbato, Michele, i Marcello Vasta. "Time-Variant Spectral Characteristics of Non-Stationary Processes". W 6th International Conference on Computational Stochastic Mechanics. Singapore: Research Publishing Services, 2011. http://dx.doi.org/10.3850/978-981-08-7619-7_p004.

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Li, Chang, i Maarten de Rijke. "Cascading Non-Stationary Bandits: Online Learning to Rank in the Non-Stationary Cascade Model". W Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/396.

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Non-stationarity appears in many online applications such as web search and advertising. In this paper, we study the online learning to rank problem in a non-stationary environment where user preferences change abruptly at an unknown moment in time. We consider the problem of identifying the K most attractive items and propose cascading non-stationary bandits, an online learning variant of the cascading model, where a user browses a ranked list from top to bottom and clicks on the first attractive item. We propose two algorithms for solving this non-stationary problem: CascadeDUCB and CascadeSWUCB. We analyze their performance and derive gap-dependent upper bounds on the n-step regret of these algorithms. We also establish a lower bound on the regret for cascading non-stationary bandits and show that both algorithms match the lower bound up to a logarithmic factor. Finally, we evaluate their performance on a real-world web search click dataset.
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Li, Yu-Lin, i Jehn-Ruey Jiang. "Anomaly Detection for Non-Stationary and Non-Periodic Univariate Time Series". W 2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE). IEEE, 2020. http://dx.doi.org/10.1109/ecice50847.2020.9301943.

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Raporty organizacyjne na temat "Non-stationary tide"

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Hart, Carl, i Gregory Lyons. A tutorial on the rapid distortion theory model for unidirectional, plane shearing of homogeneous turbulence. Engineer Research and Development Center (U.S.), lipiec 2022. http://dx.doi.org/10.21079/11681/44766.

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The theory of near-surface atmospheric wind noise is largely predicated on assuming turbulence is homogeneous and isotropic. For high turbulent wavenumbers, this is a fairly reasonable approximation, though it can introduce non-negligible errors in shear flows. Recent near-surface measurements of atmospheric turbulence suggest that anisotropic turbulence can be adequately modeled by rapid-distortion theory (RDT), which can serve as a natural extension of wind noise theory. Here, a solution for the RDT equations of unidirectional plane shearing of homogeneous turbulence is reproduced. It is assumed that the time-varying velocity spectral tensor can be made stationary by substituting an eddy-lifetime parameter in place of time. General and particular RDT evolution equations for stochastic increments are derived in detail. Analytical solutions for the RDT evolution equation, with and without an effective eddy viscosity, are given. An alternative expression for the eddy-lifetime parameter is shown. The turbulence kinetic energy budget is examined for RDT. Predictions by RDT are shown for velocity (co)variances, one-dimensional streamwise spectra, length scales, and the second invariant of the anisotropy tensor of the moments of velocity. The RDT prediction of the second invariant for the velocity anisotropy tensor is shown to agree better with direct numerical simulations than previously reported.
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