Relevant bibliographies by topics / Spectral inversion

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  2. Dissertations / Theses
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Academic literature on the topic 'Spectral inversion'

Author: Grafiati
Published: 1 April 2023

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Journal articles on the topic "Spectral inversion"

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Riethmüller, T. L., and S. K. Solanki. "The potential of many-line inversions of photospheric spectropolarimetric data in the visible and near UV." Astronomy & Astrophysics 622 (January 24, 2019): A36. http://dx.doi.org/10.1051/0004-6361/201833379.

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Our knowledge of the lower solar atmosphere is mainly obtained from spectropolarimetric observations, which are often carried out in the red or infrared spectral range and almost always cover only a single or a few spectral lines. Here we compare the quality of Stokes inversions of only a few spectral lines with many-line inversions. In connection with this, we have also investigated the feasibility of spectropolarimetry in the short-wavelength range, 3000 Å−4300 Å, where the line density but also the photon noise are considerably higher than in the red, so that many-line inversions could be particularly attractive in that wavelength range. This is also timely because this wavelength range will be the focus of a new spectropolarimeter in the third science flight of the balloon-borne solar observatory SUNRISE. For an ensemble of state-of-the-art magneto-hydrodynamical atmospheres we synthesize exemplarily spectral regions around 3140 Å (containing 371 identified spectral lines), around 4080 Å (328 lines), and around 6302 Å (110 lines). The spectral coverage is chosen such that at a spectral resolving power of 150 000 the spectra can be recorded by a 2K × 2K detector. The synthetic Stokes profiles are degraded with a typical photon noise and afterward inverted. The atmospheric parameters of the inversion of noisy profiles are compared with the inversion of noise-free spectra. We find that significantly more information can be obtained from many-line inversions than from a traditionally used inversion of only a few spectral lines. We further find that information on the upper photosphere can be significantly more reliably obtained at short wavelengths. In the mid and lower photosphere, the many-line approach at 4080 Å provides equally good results as the many-line approach at 6302 Å for the magnetic field strength and the line-of-sight (LOS) velocity, while the temperature determination is even more precise by a factor of three. We conclude from our results that many-line spectropolarimetry should be the preferred option in the future, and in particular at short wavelengths it offers a high potential in solar physics.
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Hall, R. L. "Geometric spectral inversion." Journal of Physics A: Mathematical and General 28, no. 6 (March 23, 1995): 1771–86. http://dx.doi.org/10.1088/0305-4470/28/6/028.

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Rubino, J. Germán, and Danilo Velis. "Thin-bed prestack spectral inversion." GEOPHYSICS 74, no. 4 (July 2009): R49—R57. http://dx.doi.org/10.1190/1.3148002.

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Prestack seismic data has been used in a new method to fully determine thin-bed properties, including the estimation of its thickness, P- and S-wave velocities, and density. The approach requires neither phase information nor normal-moveout (NMO) corrections, and assumes that the prestack seismic response of the thin layer can be isolated using an offset-dependent time window. We obtained the amplitude-versus-angle (AVA) response of the thin bed considering converted P-waves, S-waves, and all the associated multiples. We carried out the estimation of the thin-bed parameters in the frequency (amplitude spectrum) domain using simulated annealing. In contrast to using zero-offset data, the use of AVA data contributes to increase the robustness of this inverse problem under noisy conditions, as well as to significantly reduce its inherent nonuniqueness. To further reduce the nonuniqueness, and as a means to incorporate a priori geologic or geophysical information (e.g., well-log data), we imposed appropriate bounding constraints to the parameters of the media lying above and below the thin bed, which need not be known accurately. We tested the method by inverting noisy synthetic gathers corresponding to simple wedge models. In addition, we stochastically estimated the uncertainty of the solutions by inverting different data sets that share the same model parameters but are contaminated with different noise realizations. The results suggest that thin beds can be characterized fully with a moderate to high degree of confidence below tuning, even when using an approximate wavelet spectrum.
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Hofmann, Ryan A., Kevin P. Reardon, Ivan Milic, Momchil E. Molnar, Yi Chai, and Han Uitenbroek. "Evaluating Non-LTE Spectral Inversions with ALMA and IBIS." Astrophysical Journal 933, no. 2 (July 1, 2022): 244. http://dx.doi.org/10.3847/1538-4357/ac6f00.

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Abstract We present observations of a solar magnetic network region in the millimeter continuum with the Atacama Large Millimeter/submillimeter Array (ALMA) and in the Ca 8542 and Na 5896 Å spectral lines with the Interferometric Bidimensional Spectrometer (IBIS). Our goal is to compare the measurement of local gas temperatures provided by ALMA with the temperature diagnostics provided by non-LTE inversions using the STockholm inversion Code (STiC). In performing these inversions, we find that using column mass as the reference height scale, rather than optical depth, provides more reliable atmospheric profiles above the temperature minimum and that the treatment of non-LTE hydrogen ionization brings the inferred chromospheric temperatures into better agreement with the ALMA measurements. The Band 3 brightness temperatures are higher but well correlated spatially with the inversion-derived temperatures at the height of formation of the Ca 8542 line core. The Band 6 temperatures instead do not show good correlations with the temperatures at any specific layer in the inverted atmospheres. We then performed inversions that included the millimeter-continuum intensities as an additional constraint. Incorporating Band 3 generally resulted in atmospheres showing a strong temperature rise in the upper atmosphere, while including Band 6 led to significant regions of anomalously low temperatures at chromospheric heights. This is consistent with the idea that the Band 6 emission can come from a combination of heights ranging from the temperature minimum to upper chromosphere. The poor constraints on the chromospheric electron density with existing inversion codes introduces difficulties in determining the height(s) of formation of the millimeter continuum as well as uncertainties in the temperatures derived from the spectral lines.
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Muyzert, Everhard. "Seabed property estimation from ambient-noise recordings: Part 2 — Scholte-wave spectral-ratio inversion." GEOPHYSICS 72, no. 4 (July 2007): U47—U53. http://dx.doi.org/10.1190/1.2719062.

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Having knowledge of the near-surface shear-velocity model is useful for various seismic processing methods such as shear-wave static estimation, wavefield separation, and geohazard prediction. I present a new method to derive a 2D near-surface shear-velocity model from ambient-noise recordings made at the seafloor. The method relies on inverting horizontal- and vertical-amplitude spectra of Scholte waves propagating in the seafloor. I compare the commonly used horizontal-over-vertical spectral ratio with three alternative spectral-ratio definitions through modeling. The modeling shows that the vertical-over-total spectral ratio has some favorable properties for inversion. I describe a nonlinear inversion method for the vertical-to-total spectral ratio of the Scholte waves and apply it to an ambient-noise data set recorded by an ocean-bottom-cable (OBC) system. A 1D near-surface shear-velocity model is derived through a joint inversion of the spectral-ratio and phase-velocity data. A 2D shear-velocity model is obtained through a local inversion of the spectral ratios averaged over small groups of receivers and shows evidence for lateral heterogeneity. The newly developed method for deriving near-surface shear-velocity distribution by inverting the Scholte-wave spectral ratio measured from seabed noise provides great opportunities for estimating the shallow-seabed shear velocity in deep water. Another benefit of the method is that, with the OBC system, no additional hardware is needed; only additional recording time is required. In this case, half an hour is sufficient.
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Qi, Haixia, Bingyu Zhu, Lingxi Kong, Weiguang Yang, Jun Zou, Yubin Lan, and Lei Zhang. "Hyperspectral Inversion Model of Chlorophyll Content in Peanut Leaves." Applied Sciences 10, no. 7 (March 26, 2020): 2259. http://dx.doi.org/10.3390/app10072259.

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The purpose of this study is to determine a method for quickly and accurately estimating the chlorophyll content of peanut plants at different plant densities. This was explored using leaf spectral reflectance to monitor peanut chlorophyll content to detect sensitive spectral bands and the optimum spectral indicators to establish a quantitative model. Peanut plants under different plant density conditions were monitored during three consecutive growth periods; single-photon avalanche diode (SPAD) and hyperspectral data derived from the leaves under the different plant density conditions were recorded. By combining arbitrary bands, indices were constructed across the full spectral range (350–2500 nm) based on blade spectra: the normalized difference spectral index (NDSI), ratio spectral index (RSI), difference spectral index (DSI) and soil-adjusted spectral index (SASI). This enabled the best vegetation index reflecting peanut-leaf SPAD values to be screened out by quantifying correlations with chlorophyll content, and the peanut leaf SPAD estimation models established by regression analysis to be compared and analyzed. The results showed that the chlorophyll content of peanut leaves decreased when plant density was either too high or too low, and that it reached its maximum at the appropriate plant density. In addition, differences in the spectral reflectance of peanut leaves under different chlorophyll content levels were highly obvious. Without considering the influence of cell structure as chlorophyll content increased, leaf spectral reflectance in the visible (350–700 nm): near-infrared (700–1300 nm) ranges also increased. The spectral bands sensitive to chlorophyll content were mainly observed in the visible and near-infrared ranges. The study results showed that the best spectral indicators for determining peanut chlorophyll content were NDSI (R520, R528), RSI (R748, R561), DSI (R758, R602) and SASI (R753, R624). Testing of these regression models showed that coefficient of determination values based on the NDSI, RSI, DSI and SASI estimation models were all greater than 0.65, while root mean square error values were all lower than 2.04. Therefore, the regression model established according to the above spectral indicators was a valid predictor of the chlorophyll content of peanut leaves.
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Xue, Yun, Bin Zou, Yimin Wen, Yulong Tu, and Liwei Xiong. "Hyperspectral Inversion of Chromium Content in Soil Using Support Vector Machine Combined with Lab and Field Spectra." Sustainability 12, no. 11 (May 29, 2020): 4441. http://dx.doi.org/10.3390/su12114441.

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Chromium is not only an essential trace element for the growth and development of living organisms; it is also a heavy metal pollutant. Excessive chromium in farmland soil will not only cause harm to crops, but could also constitute a serious threat to human health through the cumulative effect of the food chain. The determination of heavy metals in tailings of farmland soil is an essential means of soil environmental protection and sustainable development. Hyperspectral remote sensing technology has good characteristics, e.g., high speed, macro, and high resolution, etc., and has gradually become a focus of research to determine heavy metal content in soil. However, due to the spectral variation caused by different environmental conditions, the direct application of the indoor spectrum to conduct field surveys is not effective. Soil components are complex, and the effect of linear regression of heavy metal content is not satisfactory. This study builds indoor and outdoor spectral conversion models to eliminate soil spectral differences caused by environmental conditions. Considering the complex effects of soil composition, we introduce a support vector machine model to retrieve chromium content that has advantages in solving problems such as small samples, non-linearity, and a large number of dimensions. Taking a mining area in Hunan, China as a test area, this study retrieved the chromium content in the soil using 12 combination models of three types of spectra (field spectrum, lab spectrum, and direct standardization (DS) spectrum), two regression methods (stepwise regression and support vector machine regression), and two factors (strong correlation factor and principal component factor). The results show that: (1) As far as the spectral types are concerned, the inversion accuracy of each combination of the field spectrum is generally lower than the accuracy of the corresponding combination of other spectral types, indicating that field environmental interference affects the modeling accuracy. Each combination of DS spectra has higher inversion accuracy than the corresponding combination of field spectra, indicating that DS spectra have a certain effect in eliminating soil spectral differences caused by environmental conditions. (2) The inversion accuracy of each spectrum type of SVR_SC (Support Vector Regression_Strong Correlation) is the highest for the combination of regression method and inversion factor. This indicates the feasibility and superiority of inversion of heavy metals in soil by a support vector machine. However, the inversion accuracy of each spectrum type of SVR_PC (Support Vector Regression_Principal Component) is generally lower than that of other combinations, which indicates that, to obtain superior inversion performance of SVR, the selection of characteristic factors is very important. (3) Through principal component regression analysis, it is found that the pre-processed spectrum is more stable for the inversion of Cr concentration. The regression coefficients of the three types of differential spectra are roughly the same. The five statistically significant characteristic bands are mostly around 384–458 nm, 959–993 nm, 1373–1448 nm, 1970–2014 nm, and 2325–2400 nm. The research results provide a useful reference for the large-scale normalization monitoring of chromium-contaminated soil. They also provide theoretical and technical support for soil environmental protection and sustainable development.
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Wang, Weiyan, Yungui Zhang, Zhihong Li, Qingli Liu, Wenqiang Feng, Yulan Chen, Hong Jiang, Hui Liang, and Naijie Chang. "Fourier-Transform Infrared Spectral Inversion of Soil Available Potassium Content Based on Different Dimensionality Reduction Algorithms." Agronomy 13, no. 3 (February 21, 2023): 617. http://dx.doi.org/10.3390/agronomy13030617.

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Estimating the available potassium (AK) in soil can help improve field management and crop production. Fourier-transform infrared (FTIR) spectroscopy is one of the most promising techniques for the fast and real-time analysis of soil AK content. However, the successful estimation of soil AK content by FTIR depends on the proper selection of appropriate spectral dimensionality reduction techniques. To magnify the subtle spectral signals concerning AK content and improve the understanding of the characteristic FTIR wavelengths of AK content, a total of 145 soil samples were collected in an agricultural site located in the southwest part of Sichuan, China, and three typical spectral dimensionality reduction methods—the successive projections algorithm (SPA), simulated annealing algorithm (SA) and competitive adaptive reweighted sampling (CARS)—were adopted to select the appropriate spectral variable. Then, partial least squares regression (PLSR) was utilized to establish AK inversion models by incorporating the optimal set of spectral variables extracted by different dimensionality reduction algorithms. The accuracy of each inversion model was tested based on the coefficient of determination (R2), root mean square error (RMSE) and mean absolute value error (MAE), and the contribution of the inversion model variables was explored. The results show that: (1) The application of spectral dimensionality reduction is a useful technique for isolating specific components of multicomponent spectra, and as such is a powerful tool to improve and expand the predicted potential of the spectroscopy of soil AK content. Compared with the SA and CARS algorithms, the SPA was more suitable for soil AK content inversion. (2) The inversion model results showed that the characteristic wavelengths were mainly around 777 nm, 1315 nm, 1375 nm, 1635 nm, 1730 nm and 3568–3990 nm. (3) Comparing the performances of different inversion models, the SPA–PLSR model (R2= 0.49, RMSE = 22.80, MAE = 16.82) was superior to the SA–PLSR and CARS–PLSR models, which has certain guiding significance for the rapid detection of soil AK content.
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Neukirch, Maik, Antonio García-Jerez, Antonio Villaseñor, Francisco Luzón, Jacques Brives, and Laurent Stehly. "On the Utility of Horizontal-to-Vertical Spectral Ratios of Ambient Noise in Joint Inversion with Rayleigh Wave Dispersion Curves for the Large-N Maupasacq Experiment." Sensors 21, no. 17 (September 4, 2021): 5946. http://dx.doi.org/10.3390/s21175946.

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Horizontal-to-Vertical Spectral Ratios (HVSR) and Rayleigh group velocity dispersion curves (DC) can be used to estimate the shallow S-wave velocity (VS) structure. Knowing the VS structure is important for geophysical data interpretation either in order to better constrain data inversions for P-wave velocity (VP) structures such as travel time tomography or full waveform inversions or to directly study the VS structure for geo-engineering purposes (e.g., ground motion prediction). The joint inversion of HVSR and dispersion data for 1D VS structure allows characterising the uppermost crust and near surface, where the HVSR data (0.03 to 10s) are most sensitive while the dispersion data (1 to 30s) constrain the deeper model which would, otherwise, add complexity to the HVSR data inversion and adversely affect its convergence. During a large-scale experiment, 197 three-component short-period stations, 41 broad band instruments and 190 geophones were continuously operated for 6 months (April to October 2017) covering an area of approximately 1500km2 with a site spacing of approximately 1 to 3km. Joint inversion of HVSR and DC allowed estimating VS and, to some extent density, down to depths of around 1000m. Broadband and short period instruments performed statistically better than geophone nodes due to the latter’s gap in sensitivity between HVSR and DC. It may be possible to use HVSR data in a joint inversion with DC, increasing resolution for the shallower layers and/or alleviating the absence of short period DC data, which may be harder to obtain. By including HVSR to DC inversions, confidence improvements of two to three times for layers above 300m were achieved. Furthermore, HVSR/DC joint inversion may be useful to generate initial models for 3D tomographic inversions in large scale deployments. Lastly, the joint inversion of HVSR and DC data can be sensitive to density but this sensitivity is situational and depends strongly on the other inversion parameters, namely VS and VP. Density estimates from a HVSR/DC joint inversion should be treated with care, while some subsurface structures may be sensitive, others are clearly not. Inclusion of gravity inversion to HVSR/DC joint inversion may be possible and prove useful.
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Cięszczyk, Sławomir. "A Multi-Band Integrated Virtual Calibration-Inversion Method for Open Path FTIR Spectrometry." Metrology and Measurement Systems 20, no. 2 (June 1, 2013): 287–98. http://dx.doi.org/10.2478/mms-2013-0025.

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Abstract This paper addresses problems arising from in situ measurement of gas content and temperature. Such measurements can be considered indirect. Transmittance or natural radiation of a gas is measured directly. The latter method (spectral radiation measurement) is often called spectral remote sensing. Its primary uses are in astronomy and in the measurement of atmospheric composition. In industrial processes, in situ spectroscopic measurements in the plant are often made with an open path Fourier Transform Infrared (FTIR) spectrometer. The main difficulty in this approach is related to the calibration process, which often cannot be carried out in the manner used in the laboratory. Spectral information can be obtained from open path spectroscopic measurements using mathematical modeling, and by solving the inverse problem. Determination of gas content based on spectral measurements requires comparison of the measured and modeled spectra. This paper proposes a method for the simultaneous use of multiple lines to determine the gas content. The integrated absorptions of many spectral lines permits calculation of the average band absorption. An inverse model based on neural networks is used to determine gas content based on mid-infrared spectra at variable temperatures.
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Dissertations / Theses on the topic "Spectral inversion"

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Orozco, M. Catalina (Maria Catalina). "Inversion Method for Spectral Analysis of Surface Waves (SASW)." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5124.

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This research focuses on estimating the shear wave velocity (Vs) profile based on the dispersion curve obtained from SASW field test data (i.e., inversion of SASW data). It is common for the person performing the inversion to assume the prior information required to constrain the problem based on his/her own judgment. Additionally, the Vs profile is usually shown as unique without giving a range of possible solutions. For these reasons, this work focuses on: (i) studying the non-uniqueness of the solution to the inverse problem; (ii) implementing an inversion procedure that presents the estimated model parameters in a way that reflects their uncertainties; and (iii) evaluating tools that help choose the appropriate prior information. One global and one local search procedures were chosen to accomplish these purposes: a pure Monte Carlo method and the maximum likelihood method, respectively. The pure Monte Carlo method was chosen to study the non-uniqueness by looking at the range of acceptable solutions (i.e., Vs profiles) obtained with as few constraints as possible. The maximum likelihood method was chosen because it is a statistical approach, which enables us to estimate the uncertainties of the resulting model parameters and to apply tools such as the Bayesian criterion to help select the prior information objectively. The above inversion methods were implemented for synthetic data, which was produced with the same forward algorithm used during inversion. This implies that all uncertainties were caused by the nature of the SASW inversion problem (i.e., there were no uncertainties added by experimental errors in data collection, analysis of the data to create the dispersion curve, layered model to represent a real 3-D soil stratification, or wave propagation theory). At the end of the research, the maximum likelihood method of inversion and the tools for the selection of prior information were successfully used with real experimental data obtained in Memphis, Tennessee.
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Set, Sze Yun. "Dispersion compensation in high bit rate transmission systems using midspan spectral inversion." Thesis, University of Southampton, 1998. https://eprints.soton.ac.uk/394393/.

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This thesis presents experimental and theoretical work on optical fibre communication systems covering dispersion compensation, short pulse generation and high speed transmission. The focus of this thesis is on dispersion compensation using the midspan spectral inversion (MSSI) technique. Experimental investigation and theoretical studies on an MSSI system suggest potential compensation of both fibre chromatic dispersion as well as fibre nonlinearity. The performance of MSSI systems is found to be limited by a few effects that cannot be compensated for by phase conjugation and a different approach has to be employed in order to overcome these factors. Optical phase conjugators are essential elements of MSSI transmission systems. Dispersion shifted fibre (DSF) and semiconductor optical amplifiers (SOA) are two of the most important nonlinear media for phase conjugation. A comparison of these two types of phase conjugator has been carried out. By using fibre Bragg grating based filters, the noise performance of the conjugators could be optimised. Computer numerical models of various optical components have been developed which could simulate the basic function of erbium-doped fibre amplifiers, optical band pass filters, optical fibres and fibre gratings. Signal transmission in single mode fibre is modelled using the split-step Fourier method to solve the nonlinear Schrödinger equation (NLSE). These numerical models can be programmed to suit different experimental setups and allow the study of various system experiment configurations. The theoretical results help to explain and provide estimated limitations to the experimental results. Experiments carried out in the laboratories have finally culminated in a 10 Gbit/s MSSI field trial in Italy. Successful transmission of 6 picosecond pulses at 10 Gbit/s over 140 km of standard installed fibre was demonstrated. The field trial proved not only the feasibility of 40 Gbit/s MSSI transmission in the final field trial but also an implication on upgradability of currently installed links around the world. A novel polarisation insensitive optical phase conjugation configuration is proposed and demonstrated. With the use of all-fibre DFB lasers as FWM pumps, the first all fibre optical phase conjugator is realised. This configuration can achieve polarisation insensitive operation with great simplicity compared to conventional methods, which are complex and of high component count. Moreover, the same configuration can be applied to an SOA with equally good performance. We have demonstrated wideband and polarisation independent phase conjugation using a highly nonlinear DSF and a long SOA. High bit-rate operation up to 40 Gbit/s and MSSI transmission over 204 km of standard fibre using these devices has also been experimentally investigated.
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Deng, Mo Ph D. Massachusetts Institute of Technology. "Deep learning with physical and power-spectral priors for robust image inversion." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127013.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 169-182).
Computational imaging is the class of imaging systems that utilizes inverse algorithms to recover unknown objects of interest from physical measurements. Deep learning has been used in computational imaging, typically in the supervised mode and in an End-to-End fashion. However, treating the machine learning algorithm as a mere black-box is not the most efficient, as the measurement formation process (a.k.a. the forward operator), which depends on the optical apparatus, is known to us. Therefore, it is inefficient to let the neural network to explain, at least partly, the system physics. Also, some prior knowledge of the class of objects of interest can be leveraged to make the training more efficient. The main theme of this thesis is to design more efficient deep learning algorithms with the help of physical and power-spectral priors.
We first propose the learning to synthesize by DNN (LS-DNN) scheme, where we propose a dual-channel DNN architecture, each designated to low and high frequency band, respectively, to split, process, and subsequently, learns to recombine low and high frequencies for better inverse conversion. Results show that the LS-DNN scheme largely improves reconstruction quality in many applications, especially in the most severely ill-posed case. In this application, we have implicitly incorporated the system physics through data pre-processing; and the power-spectral prior through the design of the band-splitting configuration. We then propose to use the Phase Extraction Neural Networks (PhENN) trained with perceptual loss, that is based on extracted feature maps from pre-trained classification neural networks, to tackle the problem of low-light phase retrieval under low-light conditions.
This essentially transfer the knowledge, or features relevant to classifications, and thus corresponding to human perceptual quality, to the image-transformation network (such as PhENN). We find that the commonly defined perceptual loss need to be refined for the low-light applications, to avoid the strengthened "grid-like" artifacts and achieve superior reconstruction quality. Moreover, we investigate empirically the interplay between the physical and con-tent prior in using deep learning for computational imaging. More specifically, we investigate the effect of training examples to the learning of the underlying physical map and find that using training datasets with higher Shannon entropy is more beneficial to guide the training to correspond better to the system physics and thus the trained mode generalizes better to test examples disjoint from the training set.
Conversely, if more restricted examples are used as training examples, the training can be guided to undesirably "remember" to produce the ones similar as those in training, making the cross-domain generalization problematic. Next, we also propose to use deep learning to greatly accelerate the optical diffraction tomography algorithm. Unlike previous algorithms that involve iterative optimization algorithms, we present significant progresses towards 3D refractive index (RI) maps from a single-shot angle-multiplexing interferogram. Last but not least, we propose to use cascaded neural networks to incorporate the system physics directly into the machine learning algorithms, while leaving the trainable architectures to learn to function as the ideal Proximal mapping associated with the efficient regularization of the data. We show that this unrolled scheme significantly outperforms the End-to-End scheme, in low-light imaging applications.
by Mo Deng.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Pappalardo, Cirino, Bernd Vollmer, and Ariane Lancon. "The star formation history of Virgo spiral galaxies. Combined spectral and photometric inversion." Phd thesis, Université de Strasbourg, 2010. http://tel.archives-ouvertes.fr/tel-00483128.

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Cette these etudie l'influence du balayage par pression dynamique sur l'histoire de la formation stellaire des galaxies spirales qui se trouvent dans des amas. Le balayage par pression dynamique est l'interaction hydrodynamique entre le milieu interstellaire (ISM) d'une galaxie spirale qui evolue dans le puits de potentiel d'un amas, et le milieu intra-amas (ICM). Si la pression dynamique exercee par l'ICM excede la force d'attraction gravitationnelle due au potentiel galactique, la galaxie perd du gaz de sa partie externe. L'amas de la Vierge constitue un laboratoire ideal pour etudier les effets de l'environnement sur l'evolution des galaxies. En effet, cet amas est riche en spirales et dynamiquement jeune. Des observations nous montrent que la quantite de gaz atomique qui se trouve dans les spirales de la Vierge est moins importante que celle des galaxies du champ. En particulier, les spirales des amas presentent des disques HI tronques. Pour celles des galaxies qui presentent aussi une distribution stellaire symetrique, le balayage par pression dynamique semblerait etre l'origine la plus probable de la troncature du gaz du disque.
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Pappalardo, Cirino. "The star formation history of Virgo spiral galaxies : combined spectral and photometric inversion." Strasbourg, 2010. https://publication-theses.unistra.fr/public/theses_doctorat/2010/PAPPALARDO_Cirino_2010.pdf.

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Cette thèse étudie l'influence du balayage par pression dynamique sur l'histoire de la formation stellaire des galaxies spirales qui se trouvent dans des amas. Le balayage par pression dynamique est l'interaction hydrodynamique entre le milieu interstellaire (ISM) d'une galaxie spirale qui évolue dans le puits de potentiel d'un amas, et le milieu intra-amas (ICM). Si la pression dynamique exercée par l'ICM excède la force d'attraction gravitationnelle due au potentiel galactique, la galaxie perd du gaz de sa partie externe. L'amas de la Vierge constitue un laboratoire idéal pour étudier les effets de l'environnement sur l'évolution des galaxies. En effet, cet amas est riche en spirales et dynamiquement jeune. Des observations nous montrent que la quantité de gaz atomique qui se trouve dans les spirales de la Vierge est moins importante que celle des galaxies du champ. En particulier, les spirales de la Vierge est moins importante que celle des galaxies du champ. En particulier, les spirales des amas présentent des disques HI tronqués (Giovanelli & Haynes 1983). Pour celles des galaxies qui présentent aussi une distribution stellaire symétrique, le balayage par pression dynamique semblerait être l'origine la plus probable de la troncature du gaz du disque
This thesis investigates the influence of ram pressure stripping on the star formation history of cluster spiral galaxies. Ram pressure stripping is the hydrodynamical interaction between the interstellar medium (ISM) of a spiral galaxy that is moving inside the potential well of a cluster, and the intracluster medium (ICM). If the dynamical pressure exerted by the ICM is larger than the restoring force due to the galactic potential, the galaxy loses gas from the outer disk. The Virgo cluster is an ideal laboratory to study environmental effects on galaxy evolution, because it is rich in spirals and dynamically young. From observations we know that the amount of atomic gas in Virgo spirals is less than that of galaxies in the field. In particular cluster spirals show truncated HI disks (Giovanelli & Haynes 1983, Cayatte et al. 1990). For those galaxies that also show a symmetrical stellar distribution, ram pressure stripping is the most probably origin of the gas-disk truncation
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OLIVEIRA, OTAVIO KAMINSKI DE. "INVERSION OF NONLINEAR PERTURBATIONS OF THE LAPLACIAN IN GENERAL DOMAINS WITH FINITE SPECTRAL INTERACTION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=27930@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
Consideramos a análise numérica de perturbações não lineares do Laplaciano definido em regiões limitadas tratáveis pelo Método de Elementos Finitos. Supomos que as não linearidades interagem com k autovalores do Laplaciano livre. Apresentamos uma redução do problema à inversão de uma função de k variáveis e delineamos uma técnica para tal. O texto é uma extensão dos trabalhos de Cal Neto, Malta, Saldanha e Tomei.
We consider the numerical analysis of nonlinear perturbations of the Laplacian defined in limited regions amenable to the Finite Element Method. The nonlinearities are supposed to interact only with k eigenvalues of the free Laplacian. We present a reduction of the problem to the inversion of a function of k variables and indicate a technique to do so. The text extends the works by Cal Neto, Malta, Saldanha and Tomei.
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Reine, Carl Andrew. "A robust prestack Q-Inversion in the T-p Domain using variable-window spectral estimates." Thesis, University of Leeds, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511145.

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Fernandez, Cesar Aaron Moya. "Two alternative inversion techniques for the determination of seismic site response and propagation-path velocity structure : spectral inversion with reference events and neural networks." 京都大学 (Kyoto University), 2004. http://hdl.handle.net/2433/147831.

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Markusson, Ola. "Model and System Inversion with Applications in Nonlinear System Identification and Control." Doctoral thesis, KTH, Signals, Sensors and Systems, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3287.

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Ghorbani, Ahmad. "Contribution au développement de la résistivité complexe et à ses applications en environnement." Paris 6, 2007. http://www.theses.fr/2007PA066607.

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Ce mémoire est divisé en deux chapitres. Le premier chapitre présente une synthèse bibliographique sur la méthode de Polarisation Provoquée (PP). Il passe en revue les derniers résultats théoriques et expérimentaux et insiste sur les applications environnementales de la méthode Polarisation Provoquée Spectrale (PPS ou Spectral Induced Polarization ou SIP en anglais), encore souvent appelée résistivité complexe. Le deuxième chapitre comprend cinq sous-chapitres. Dans un premier sous-chapitre, l'approche bayésienne est développée pour inverser les paramètres du modèle de Cole-Cole dans les domaines temporel et fréquentiel. Nous avons évalué la pertinence et la robustesse de la méthode des moindres carrés pour l’inversion des données issues de la méthode PP. Les résultats montrent que l'approche classique dans le domaine temporel ne peut pas mener à une évaluation appropriée des paramètres Cole-Cole. L'emploi harmonique de signal carré injecté à fin d’obtenir un plus large spectre n’est pas non plus satisfaisant. À l'opposé, les paramètres Cole-Cole sont mieux inversés dans le domaine fréquentiel. Dans un deuxième sous-chapitre, nous avons conçu un algorithme d'inversion 1D par homotopie pour récupérer les paramètres du modèle Cole-Cole à partir des données de PPS. Cet algorithme permet de découpler les effets associés à la seule PP de ceux issus de couplages électromagnétiques parasites se produisant dans une large bande de fréquences. Nous avons employé le code numérique, CR1Dmod, développé initialement par Ingeman-Nielsen et Baumgartner (2006), résout le problème direct. L’interface utilisateur graphique, que nous avons conçue, facilite les entrées des données et des paramètres du modèle a priori, ainsi que la définition de la configuration géométrique du dispositif (géométrie des câbles). Nous présentons deux exemples synthétiques pour illustrer la récupération des paramètres spectraux à partir de données de résistivités complexes. Dans un troisième sous-chapitre, la PPS est appliquée pour le suivi de l'infiltration d'eau dans un sol limoneux-argileux. L’infiltration a été réalisée à partir d’une pluie artificielle (à débit de pluie quasi-constant) et au cours de deux expérimentations, l’une menée in situ et l’autre sur une colonne de sol. Les expériences ont été basées sur l'acquisition couplée de données de tensiomètres et de spectres de PPS durant l’infiltration. Cette approche a confirmé l'existence d'une baisse significative de la phase (ou de la conductivité imaginaire) dans la partie haute fréquence du spectre (typiquement, 1-12 kHz) qui a été corrélée avec le remplissage d’eau dans des pores de diamètres compris dans la gamme de [30-85] m. Ces baisses de phase sont interprétées comme un effet de type Maxwell-Wagner. Les résultats de cette étude suggèrent que la méthode PPS serait en mesure de fournir des informations sur le remplissage par l'eau des plus gros pores et ainsi d’estimer indirectement des propriétés structurales. Dans un quatrième sous-chapitre, la mesure de la résistivité complexe est employée pour le suivi de la teneur en eau et des microfissures induites thermiquement sur des échantillons quasi-saturés d'argillite. Les mesures de PPS ont été enregistrées durant deux trajets consécutifs en dessiccation: (a) le premier trajet a consisté en une phase de désaturation à l'air ambiant et (b) durant le deuxième trajet, les échantillons ont été soumis à quatre paliers de chauffe (température égale à 70, 80, 90 et 105 °C). Durant la phase de désaturation, l'amplitude de la résistivité complexe a été extrêmement sensible au changement de teneur en eau (un facteur de 3 à 5). Pendant la phase de chauffage, la résistivité a augmenté de deux ordres de grandeur comparativement à l'état initial. Les modèles Cole-Cole et Cole-Cole Généralisé sont les meilleurs modèles pour inverser respectivement les données de PPS pour la phase de désaturation et la phase de chauffage. Cependant, les résultats prouvent que le développement de l'anisotropie et les changements par conséquent de texture peuvent induire différentes signatures spectrales et processus de polarisation. Dans le dernier sous-chapitre, le modèle empirique de Cole-Cole qui est très largement utilisé dans les études PP est employé pour l'étude de la compaction par dissolution sous contrainte de formations sédimentaires. Notre contribution dans cette étude a consisté à écrire l'algorithme nécessaire à l’application du modèle de Cole-Cole dans le domaine temporel.
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Books on the topic "Spectral inversion"

1

Data inversion algorithm development for the hologen [i.e. halogen] occultation experiment. [Williamsburg, Va.?]: College of William and Mary, 1987.

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Myers, Timothy F. Proposed implementation of a near-far resistant multiuser detector without matrix inversion using Delta-Sigma modulation. 1992.

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Brown, Derek H. Projectivism and Phenomenal Presence. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199666416.003.0010.

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Projectivism asserts that we project subjective aspects of perception into what we experience as the world outside ourselves. It is minimally familiar from various phantom pains, afterimages, and hallucinations. Views like sense-datum theory arguably assert a more global, Strong Projectivism: all perceptual experiences involve and only involve direct awareness of projected elements. Strong Projectivism is an underappreciated variety of intentionalism. It straightforwardly explains the transparency of experience, and phenomena qualia theorists offer to avoid intentionalism, including blurry vision and spectrum inversion. Finally, projectivism illuminates residual qualia-friendly cases involving imagination and emotion. Although some cases may provide instances of non-projected, non-intentional aspects of experience, most do not. Thus, the notion of phenomenal presence drawn from projectivism does justice to a great many of the forces at play in debates surrounding qualia and intentionalism. We should bound toward Strong Projectivism.
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Book chapters on the topic "Spectral inversion"

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Fichtner, Andreas. "Spectral-Element Methods." In Full Seismic Waveform Modelling and Inversion, 59–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_4.

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Leeb, H., H. Fiedeldey, R. Lipperheide, and W. A. Schnizer. "Inversion of Three-Quark Spectral Data." In Inverse Problems and Theoretical Imaging, 356–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75298-8_44.

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Kurtuluş, C., and M. Alpmen. "Spectral Analysis of Blast Vibrations from Large Explosions." In Theory and Practice of Geophysical Data Inversion, 283–308. Wiesbaden: Vieweg+Teubner Verlag, 1992. http://dx.doi.org/10.1007/978-3-322-89417-5_18.

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Hori, Muneo. "Inversion Method Using Spectral Decomposition of Green’s Function." In IUTAM Symposium on Field Analyses for Determination of Material Parameters — Experimental and Numerical Aspects, 123–37. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-010-0109-0_12.

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Fiedeldey, H. "Inversion at Fixed-Energy for Nonlocal and Algebraic Potentials and N-Body Spectral Inversion." In Lecture Notes in Physics, 176–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-662-13969-1_12.

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Fiedeldey, H. "Inversion at fixed-energy for nonlocal and algebraic potentials and N-body spectral inversion." In Lecture Notes in Physics, 176–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-57576-6_12.

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Mecozzi, Antonio. "Devices for all-optical wavelength conversion and spectral inversion." In Optical Networks: Design and Modelling, 25–29. New York, NY: Springer US, 1999. http://dx.doi.org/10.1007/978-0-387-35398-2_3.

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Socas-Navarro, Héctor. "Non-LTE Inversion of Spectral Lines and Stokes Profiles." In Highlights of Spanish Astrophysics II, 233–40. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-017-1776-2_55.

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Cuomo, V., U. Amato, R. Rizzi, C. Serio, and V. Tramutoli. "Topics in Optimal Inversion Schemes Applied to Atmospheric Structure Retrieval." In High Spectral Resolution Infrared Remote Sensing for Earth’s Weather and Climate Studies, 163–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84599-4_11.

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Horvath, H., F. J. Olmo, L. Alados Arboledas, O. Jovanovic, M. Gangl, W. Kaller, C. Sanchez, H. Sauerzopf, and S. Seidl. "Size Distributions of Particles Obtained by Inversion of Spectral Extinction and Scattering Measurements." In Optics of Cosmic Dust, 143–58. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0628-6_9.

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Conference papers on the topic "Spectral inversion"

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Maulana, A. D. "Seismic Inversion Resolution Enhancement With (3S) Spectral Blueing, Spectral Balancing, and Stochastic Inversion on Fluvio Deltaic Environment." In Indonesian Petroleum Association - 46th Annual Convention & Exhibition 2022. Indonesian Petroleum Association, 2022. http://dx.doi.org/10.29118/ipa22-g-126.

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The accuracy of the geomodelling stage is vital in the exploration and development of oil and gas fields. One of the many factors that can improve the precision of the modeling is seismic inversion. As secondary data in estimating collocated co-kriging, seismic inversion is notable. The results of seismic inversions are often limited in terms of resolution. It is precarious if it is still used for rock property modeling because of the inability to separate subsurface geological events. Therefore, this research offers an integrated seismic inversion enhancement method, namely the 3S method. Using a combination of 3S, namely Spectral Blueing, Spectral Balancing, and Stochastic Inversion, it is expected to give a solution in overcoming issues in thin-bed seismic inversion. Spectral Blueing aims to increase the dominance of Blue Spectrum by analyzing the slope spectrum of the well data, bandpassing, and analyzing the deconvolution operator. In this method, the spectrum of the well data is used to analyze the slope of the blue spectrum component, which is absent in seismic data in general. This process will produce a deconvolution operator wavelet that increases the amplitude spectrum in the blue spectrum area. In addition, spectral balancing is a feature that can balance the shape of the amplitude spectrum to resemble a plateau shape. This approach's base is bandpassing in a few frequency ranges combined with each frequency's amplitude normalization process. This approach aims to equalize the dominance in each spectrum interval. The final result will be a volume merging spectrum to re-unite it into a more balanced seismic spectral cube. The seismic inversion model is applied based on seismic data with better blue spectrum dominance. The data inversion process can be maximized at the upper limit of the seismic spectrum by using this method's output. The improved resolution was further improved using the Stochastic Inversion method by performing a geostatistics-based seismic inversion and realization with the results of a model-based inversion as a trend guide for input data. A variogram model is required to provide an anisotropic constraint on the inversion results. They are using a deterministic inverted cube as the initial lateral variogram model and upscaling well data as the actual vertical variogram model. A total of 5 stochastic seismic inversion realizations have been produced. QC and QA are performed on each inversion result to ensure the inversion results have good reliability. Reliability analysis was carried out using the Method of RMS error, coefficient of determination, and property difference. The forward modeled seismic is compared with the actual seismic, and the inverted acoustic impedance is performed with the actual acoustic impedance. It can be seen that the seismic enhancement method can significantly increase the wellness and seismicity correlation. In addition, stochastic enhancement can effectively improve the correlation of wells by providing options for geostatistical uncertainty outputs. This method provides the advantage of increasing multiple resolutions by maximizing seismic data and carrying out geostatistics realization. So that anomalies and subsurface geological events can be separated and described optimally.
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HALL, RICHARD L. "GEOMETRIC SPECTRAL INVERSION." In Proceedings of the 13th Regional Conference. World Scientific Publishing Company, 2012. http://dx.doi.org/10.1142/9789814417532_0001.

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Swiatlowski, J., and W. Leoński. "Short pulse-induced population inversion for continuum-continuum transitions." In Spectral line shapes. AIP, 1990. http://dx.doi.org/10.1063/1.39932.

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Sharma, Anshuman, Vishnu Kishore Pai, and N. Reviraj. "Spectral inversion in QPSK receiver." In 2016 International conference on Signal Processing, Communication, Power and Embedded System (SCOPES). IEEE, 2016. http://dx.doi.org/10.1109/scopes.2016.7955766.

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Ning, Chengda, Xianyong Jing, Zhihuan Lan, and Chunyan Tian. "Spectral measuring temperature inversion study." In 2016 2nd Workshop on Advanced Research and Technology in Industry Applications (WARTIA-16). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/wartia-16.2016.76.

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Zhou*, Donghong, Bo Wang, Zhanghong Shen, and Gang Peng. "Geostatistical spectral inversion: The thin layer study using spectral inversion method with geostatistical information." In SEG Technical Program Expanded Abstracts 2014. Society of Exploration Geophysicists, 2014. http://dx.doi.org/10.1190/segam2014-0666.1.

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Boardman, Joseph W. "Inversion of high spectral resolution data." In Imaging Spectroscopy of the Terrestrial Environment, edited by Gregg Vane. SPIE, 1990. http://dx.doi.org/10.1117/12.21355.

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Chen, Siyuan, Siyuan Cao, Yaoguang Sun, and Yumeng Jiang. "Nonstationary spectral inversion of seismic data." In First International Meeting for Applied Geoscience & Energy. Society of Exploration Geophysicists, 2021. http://dx.doi.org/10.1190/segam2021-3583203.1.

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Bonar, David C., and Mauricio D. Sacchi. "Complex spectral decomposition via inversion strategies." In SEG Technical Program Expanded Abstracts 2010. Society of Exploration Geophysicists, 2010. http://dx.doi.org/10.1190/1.3513105.

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Lazaratos, Spyros, and Roy L. David. "Inversion by pre‐migration spectral shaping." In SEG Technical Program Expanded Abstracts 2009. Society of Exploration Geophysicists, 2009. http://dx.doi.org/10.1190/1.3255338.

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Reports on the topic "Spectral inversion"

1

Yeh. Spectral Logic Inversion Using Optical Wave Mixing. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada307495.

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White, H. P., J. C. Deguise, J. W. Schwarz, R. Hitchcock, and K. Staenz. Defining Shaded Spectra by Model Inversion for Spectral Unmixing of Hyperspectral Datasets - Theory and Preliminary Application. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2002. http://dx.doi.org/10.4095/219895.

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Baumgardt, Douglas R., and Angelina Freeman. Characterization of Underwater Explosions by Spectral/Cepstral Analysis, Modeling and Inversion. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada443931.

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Desbarats, A. J. An iterative least-square method for the inversion of spectral radiometric data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128069.

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Griem, H. Experimental study of population inversion and spectral line broadening in a plasma containing a mixture of high Z and low Z ions. Office of Scientific and Technical Information (OSTI), October 1988. http://dx.doi.org/10.2172/7264387.

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Author, Not Given. Source Spectra Analysis of SPE Phase I from Frequency-Domain Moment Tensor Inversion. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1407858.

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