Journal articles: 'Spectral fitting method'

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Yang, Yong, Lei Wang, and Chuan Zheng Zhu. "Equivalent Brightness Fitting Calculation Method about White LEDs." Applied Mechanics and Materials 121-126 (October 2011): 2721–25. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.2721.

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White LEDs can show different correlated color temperature (abbreviated as CCT) by adjusting the luminous spectrum peak distribution and relative strength. Recent research results indicate that spectral luminous efficiency function of mesopic vision Vmes(λ) and equivalent brightness are associated with luminous spectra of light sources. A series of white LEDs with different CCT are tested and calculated, it shows white LED with higher CCT has higher mesopic vision equivalent brightness, although the brightness are identical when the tester corrected by traditional photopic vision spectral luminous efficiency V(λ). From the equivalent brightness curve fitting, the curve can be described as a polynomial function, for it excellent correlation, the more value of equivalent brightness could be calculated without complex derivation.

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Zhang, Liu, Jiakun Zhang, Hongzhen Song, Wen Zhang, and Wenhua Wang. "Case Study on the Fitting Method of Typical Objects." Photonics 8, no. 10 (October 9, 2021): 432. http://dx.doi.org/10.3390/photonics8100432.

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This study proposes different fitting methods for different types of targets in the 400–900 nm wavelength range, based on convex optimization algorithms, to achieve the effect of high-precision spectral reconstruction for small space-borne spectrometers. This article first expounds on the mathematical model in the imaging process of the small spectrometer and discretizes it into an AX=B matrix equation. Second, the design basis of the filter transmittance curve is explained. Furthermore, a convex optimization algorithm is used, based on 50 filters, and appropriate constraints are added to solve the target spectrum. First, in terms of spectrum fitting, six different ground object spectra are selected, and Gaussian fitting, polynomial fitting, and Fourier fitting are used to fit the original data and analyze the best fit of each target spectrum. Then the transmittance curve of the filter is equally divided, and the corresponding AX=B discrete equation set is obtained for the specific object target, and a random error of 1% is applied to the equation set to obtain the discrete spectral value. The fitting is performed for each case to determine the best fitting method with errors. Subsequently, the transmittance curve of the filter with the detector characteristics is equally divided, and the corresponding AX=B discrete equation set is obtained for the specific object target. A random error of 1% is applied to the equation set to obtain the error. After the discrete spectral values are obtained, the fitting is performed again, and the best fitting method is determined. In order to evaluate the fitting accuracy of the original spectral data and the reconstruction accuracy of the calculated discrete spectrum, the three evaluation indicators MSE, ARE, and RE are used for evaluation. To measure the stability and accuracy of the spectral reconstruction of the fitting method more accurately, it is necessary to perform 500 cycles of calculations to determine the corresponding MSE value and further analyze the influence of the fitting method on the reconstruction accuracy. The results show that different fitting methods should be adopted for different ground targets under the error conditions. The three indicators, MSE, ARE, and RE, have reached high accuracy and strong stability. The effect of high-precision reconstruction of the target spectrum is achieved. This article provides new ideas for related scholars engaged in hyperspectral reconstruction work and promotes the development of hyperspectral technology.

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Bluteau, Cynthia E., Nicole L. Jones, and Gregory N. Ivey. "Estimating Turbulent Dissipation from Microstructure Shear Measurements Using Maximum Likelihood Spectral Fitting over the Inertial and Viscous Subranges." Journal of Atmospheric and Oceanic Technology 33, no. 4 (April 2016): 713–22. http://dx.doi.org/10.1175/jtech-d-15-0218.1.

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AbstractA technique is presented to derive the dissipation of turbulent kinetic energy ϵ by using the maximum likelihood estimator (MLE) to fit a theoretical or known empirical model to turbulence shear spectral observations. The commonly used integration method relies on integrating the shear spectra in the viscous range, thus requiring the resolution of the highest wavenumbers of the turbulence shear spectrum. With current technology, the viscous range is not resolved at sufficiently large wavenumbers to estimate high ϵ; however, long inertial subranges can be resolved, making spectral fitting over both this subrange and the resolved portion of the viscous range an attractive method for deriving ϵ. The MLE takes into account the chi-distributed properties of the spectral observations, and so it does not rely on the log-transformed spectral observations. This fitting technique can thus take advantage of both the inertial and viscous subranges, a portion of both, or simply one of the subranges. This flexibility allows a broad range of ϵ to be resolved. The estimated ϵ is insensitive to the range of wavenumbers fitted with the model, provided the noise-dominated portion of the spectra and the low wavenumbers impacted by the mean flow are avoided. For W kg−1, the MLE fitting estimates agree with those obtained by integrating the spectral observations. However, with increasing ϵ the viscous subrange is not fully resolved and the integration method progressively starts to underestimate ϵ compared with the values obtained from fitting the spectral observations.

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Carpenter, M. H., J. G. Jernigan, P. Beiersdorfer, and G. V. Brown. "The photon clean method: an event-based approach to analyzing X-ray spectra." Canadian Journal of Physics 86, no. 1 (January 1, 2008): 245–50. http://dx.doi.org/10.1139/p07-153.

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The Photon Clean Method (PCM) is an inverse Monte-Carlo method of spectral fitting that differs from traditional fitting routines found in spectral modeling packages by fitting event lists as opposed to binned spectra. The model spectrum is represented in event form as well. Thus, using this method it is possible to fit data of higher dimensionality than can be fit using binned spectra and standard routines based on Chi-Square statistics, such as event-mode data from electron beam ion traps or satellite observations that are tagged, for example, as a function of time, position, or energy. To demonstrate some of the power of the PCM and aid in its development, we have implemented a simplified one-dimensional version of the PCM algorithm (PCM1D). Using our implementation, which is a command-line program intended for public release, we have performed tests on simulated and observed Chandra ACIS CCD data, and present two examples, one on Cassiopeia A and another on a simulated multitemperature plasma in collisional ionization equilibrium. PACS No.: 52.65.Pp

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Gill, S., P. F. L. Maxted, and B. Smalley. "The atmospheric parameters of FGK stars using wavelet analysis of CORALIE spectra." Astronomy & Astrophysics 612 (April 2018): A111. http://dx.doi.org/10.1051/0004-6361/201731954.

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Context. Atmospheric properties of F-, G- and K-type stars can be measured by spectral model fitting or with the analysis of equivalent width (EW) measurements. These methods require data with good signal-to-noise ratios (S/Ns) and reliable continuum normalisation. This is particularly challenging for the spectra we have obtained with the CORALIE échelle spectrograph for FGK stars with transiting M-dwarf companions. The spectra tend to have low S/Ns, which makes it difficult to analyse them using existing methods. Aims. Our aim is to create a reliable automated spectral analysis routine to determine Teff, [Fe/H], V sini from the CORALIE spectra of FGK stars. Methods. We use wavelet decomposition to distinguish between noise, continuum trends, and stellar spectral features in the CORALIE spectra. A subset of wavelet coefficients from the target spectrum are compared to those from a grid of models in a Bayesian framework to determine the posterior probability distributions of the atmospheric parameters. Results. By testing our method using synthetic spectra we found that our method converges on the best fitting atmospheric parameters. We test the wavelet method on 20 FGK exoplanet host stars for which higher-quality data have been independently analysed using EW measurements. We find that we can determine Teff to a precision of 85 K, [Fe/H] to a precision of 0.06 dex and V sini to a precision of 1.35 km s−1 for stars with V sini ≥ 5 km s−1. We find an offset in metallicity ≈− 0.18 dex relative to the EW fitting method. We can determine log g to a precision of 0.13 dex but find systematic trends with Teff. Measurements of log g are only reliable enough to confirm dwarf-like surface gravity (log g ≈ 4.5). Conclusions. The wavelet method can be used to determine Teff, [Fe/H], and V sini for FGK stars from CORALIE échelle spectra. Measurements of log g are unreliable but can confirm dwarf-like surface gravity. We find that our method is self consistent, and robust for spectra with S∕N ⪆ 40.

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Eskola, Sisko Maria, and Folke Stenman. "Interpolation of Spectral Data Using the Shift Theorem of the Discrete Fourier Transform." Applied Spectroscopy 51, no. 8 (August 1997): 1179–84. http://dx.doi.org/10.1366/0003702971941719.

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We present a method for interpolating discrete spectral data using the shift theorem of the discrete Fourier transform. The advantages of the method as compared to ordinary curve fitting and similar direct interpolation methods are that, being based on the discrete Fourier transform, our method is also very fast for large sample volumes if used with the fast Fourier transform (FFT) algorithm. In contrast to direct interpolation methods in spectral space, our method does not modify the modulus of the inverse Fourier transform of the shifted profile, so that the spectral content of the signal is preserved. The basis of the method also makes it suitable for analyzing hot-band structures in vibrational spectra. The method is illustrated with two examples.

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Ewans, K. C., E. M. Bitner-Gregersen, and C. Guedes Soares. "Estimation of Wind-Sea and Swell Components in a Bimodal Sea State." Journal of Offshore Mechanics and Arctic Engineering 128, no. 4 (December 18, 2004): 265–70. http://dx.doi.org/10.1115/1.2166655.

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Methods for separating the spectral components and describing bimodal wave spectra are evaluated with reference to wave spectra from directional wave measurements made at the Maui location off the west coast of New Zealand. Two methods involve partitioning bimodal wave spectra into wind-sea and swell components and then fitting a spectral function to each component, while the third assigns an average spectral shape based on the integrated spectral parameters. The partitioning methods involve separating the wave spectrum into two frequency bands: a low-frequency peak, the swell component, and a high-frequency peak, the wind-sea. One partitioning method uses only the frequency spectrum while the other analyzes the complete frequency-direction spectrum. Comparison of the spectral descriptions and derived parameters against the measured counterparts provides insight into the accuracy of the different approaches to describing actual bimodal sea states.

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Wu, Hao, Qing Wang, Liang Zhou, and Jin Meng. "Spectral fitting method for designing radar sequence with spectral nulling and correlation constraints." IET Radar, Sonar & Navigation 12, no. 11 (November 2018): 1260–67. http://dx.doi.org/10.1049/iet-rsn.2018.5171.

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Zhu, Xiaolan, Ya Dai, Changguo Wang, and Lanlan Tan. "Quantitative and Structure Analysis of Cellulose in Tobacco by 13C CP / MAS NMR Spectroscopy." Beiträge zur Tabakforschung International/Contributions to Tobacco Research 27, no. 3 (July 1, 2016): 126–35. http://dx.doi.org/10.1515/cttr-2016-0014.

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SUMMARY A new method utilizing 13C cross-polarization/magic angle spinning (CP/MAS) nuclear magnetic resonance (NMR) spectra was developed for the simultaneous quantitative determination and structure analysis of tobacco cellulose from hot water or acid detergent extraction. A reference spectrum of tobacco noncellulose components was subtracted from the spectrum of each sample to obtain a subspectrum of the cellulose components. The NMR spectra in combination with spectral fitting were analyzed in detail and some parameters, such as the content of cellulose, crystallinity, allomorph composition and lateral dimensions for cellulose elementary fibrils and microfibrils were determined. The quantitative results showed that the average recovery was 94.0% with a relative standard deviation (RSD) of 4.6–4.8%. The structure results obtained by the spectral fitting for the cellulose C1-region showed that the main allomorph composition in tobacco cellulose was Iβ. The cellulose crystallinity calculated by the spectral fitting in C4 -region was about 50%. The lateral dimensions for cellulose elementary fibrils and microfibrils were in the range of 3.0–6.0 nm and 6.0–13.0 nm, respectively. Therefore, this NMR method could provide important information on both amount and structure of cellulose in tobacco.

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Zhu, Jianxiong, Charles K. Mann, and Thomas J. Vickers. "Simultaneous Dual-Window Measurements with a Linear Photodiode Array Detector." Applied Spectroscopy 42, no. 8 (November 1988): 1567–71. http://dx.doi.org/10.1366/0003702884429733.

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A generally applicable method is described for simultaneous measurement of reference and analyte spectral features which would not otherwise fall within the range covered by a single linear diode array detector. The method employs dual entrance slits on the spectrometer to cause two spectral windows to overlap on the detector. The method is demonstrated for fluorescence measurement of Rhodamine B in ethanol. Recovery of the spectral information from the overlapped spectra using a least-squares fitting procedure is demonstrated. The simultaneously recorded reference measurements are shown to be effective in correcting for excitation source intensity variation by comparing corrected and uncorrected excitation spectra and calibration curve data.

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Chen, Xiaojing, Yongjie Lai, Xi Chen, Yijian Shi, and Dehua Zhu. "A novel spectral multivariate calibration approach based on a multiple fitting method." Analyst 141, no. 20 (2016): 5759–66. http://dx.doi.org/10.1039/c6an01201a.

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This paper introduces a novel multivariate regression approach based on a multiple fitting algorithm that combines fitting functions to accordingly configure different regression models for the quantitative analysis of spectra data.

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FU, Qiang, Wai-Shing LUK, Jun TAO, Changhao YAN, and Xuan ZENG. "Characterizing Intra-Die Spatial Correlation Using Spectral Density Fitting Method." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E92-A, no. 7 (2009): 1652–59. http://dx.doi.org/10.1587/transfun.e92.a.1652.

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Bi, Zhaoqiang, Angela P. Bruner, Jian Li, Katherine N. Scott, Zheng-She Liu, Christine B. Stopka, Hee-Won Kim, and David C. Wilson. "Spectral Fitting of NMR Spectra Using an Alternating Optimization Method with a Priori Knowledge." Journal of Magnetic Resonance 140, no. 1 (September 1999): 108–19. http://dx.doi.org/10.1006/jmre.1999.1833.

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Luo, Liezhao, Ting Li, Jiangge Deng, Runzhou Zhao, and Jinkui Wang. "An Improved WMS-2f/1f Spectral Fitting Method Using Orthogonal Test in Initial Parameters Selection." Sensors 22, no. 19 (September 30, 2022): 7430. http://dx.doi.org/10.3390/s22197430.

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This paper proposes an improved wavelength modulation spectroscopy with the 2nd harmonics normalized by the 1st harmonics (WMS-2f/1f) spectral fitting method using the orthogonal test in selection of the initial parameters. The method is implemented and validated experimentally in measurement of the temperature of diluted H2O in air (1 atm, 291K, 0.7%) by the WMS-2f/1f technique. The transition center wavelength targets near 1344 nm. Results demonstrate that the sum-square-error (SSE) between the calculated and measured WMS-2f/1f spectral profiles decreases significantly within given updating times when the optimized initial parameters are used. Compared to the conventional method, the optimized initial parameters can make the fitting routine converge more efficiently. The temperature of the vapor inferred from the proposed spectral fitting method are in good agreement with the true values.

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Zhou, Yun Ting, Xiao Ping Du, and Ming Zhe Li. "A New Method for Spectral Matching Pretreatment." Applied Mechanics and Materials 556-562 (May 2014): 527–30. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.527.

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Since spectral curves were obtained by experiment, on the basis of the fully use of the waveform characters, a new method for spectral matching pretreatment has been proposed in this paper. Corresponding to the spectral curve, we can accurately get the spectral absorption curve of the number of bands, it can effectively suppress the effects of the noise according to the times of fitting the points. Besides, it can also prominent the peak point of the material. This method can have an effective influence on the initial period of spectral match and detailed resolution; some numerical simulations have been made to test the validity and capability of the proposed method.

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Zahedi, A., and M. H. Kahaei. "Frequency Estimation of Irregularly Sampled Data Using a Sparsity Constrained Weighted Least-Squares Approach." Engineering, Technology & Applied Science Research 3, no. 1 (February 11, 2013): 368–72. http://dx.doi.org/10.48084/etasr.187.

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In this paper, a new method for frequency estimation of irregularly sampled data is proposed. In comparison with the previous sparsity-based methods where the sparsity constraint is applied to a least-squares fitting problem, the proposed method is based on a sparsity constrained weighted least-squares problem. The resulting problem is solved in an iterative manner, allowing the usage of the solution obtained at each iteration to determine the weights of the least-squares fitting term at the next iteration. Such an appropriate weighting of the least-squares fitting term enhances the performance of the proposed method. Simulation results verify that the proposed method can detect the spectral peaks using a very short data record. Compared to the previous one, the proposed method is less probable to miss the actual spectral peaks and exhibit spurious peaks.

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Li, Da-Wei, Lei Bruschweiler-Li, Alexandar L. Hansen, and Rafael Brüschweiler. "DEEP Picker1D and Voigt Fitter1D: a versatile tool set for the automated quantitative spectral deconvolution of complex 1D-NMR spectra." Magnetic Resonance 4, no. 1 (February 8, 2023): 19–26. http://dx.doi.org/10.5194/mr-4-19-2023.

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Abstract. The quantitative deconvolution of 1D-NMR spectra into individual resonances or peaks is a key step in many modern NMR workflows as it critically affects downstream analysis and interpretation. Depending on the complexity of the NMR spectrum, spectral deconvolution can be a notable challenge. Based on the recent deep neural network DEEP Picker and Voigt Fitter for 2D NMR spectral deconvolution, we present here an accurate, fully automated solution for 1D-NMR spectral analysis, including peak picking, fitting, and reconstruction. The method is demonstrated for complex 1D solution NMR spectra showing excellent performance also for spectral regions with multiple strong overlaps and a large dynamic range whose analysis is challenging for current computational methods. The new tool will help streamline 1D-NMR spectral analysis for a wide range of applications and expand their reach toward ever more complex molecular systems and their mixtures.

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Li, Changjun, Guiliang Li, and Gang Liu. "A peak fitting method for 29Si nuclear magnetic resonance spectra based on singular spectral analysis." IOP Conference Series: Materials Science and Engineering 493 (March 22, 2019): 012018. http://dx.doi.org/10.1088/1757-899x/493/1/012018.

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Liu Minghui, 刘铭晖, 董作人 Dong Zuoren, 辛国锋 Xin Guofeng, 孙延光 Sun Yanguang, 戴艳 Dai Yan, 瞿荣辉 Qu Ronghui, and 魏芳 Wei Fang. "Discrimination Method of Raman Spectral Peaks Based on Voigt Function Fitting." Chinese Journal of Lasers 44, no. 5 (2017): 0511003. http://dx.doi.org/10.3788/cjl201744.0511003.

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Minty, Brian R. S. "Multichannel models for the estimation of radon background in airborne gamma‐ray spectrometry." GEOPHYSICS 63, no. 6 (November 1998): 1986–96. http://dx.doi.org/10.1190/1.1444492.

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Adequate background correction is a crucial step in processing airborne gamma‐ray spectrometric data because any errors are amplified during subsequent processing procedures. Two multichannel models for the estimation of atmospheric radon background are proposed. The spectral‐ratio method uses the relative heights of uranium (U) series photopeaks to estimate the contribution of atmospheric radon to observed spectra. The full‐spectrum method estimates the atmospheric radon contribution through the weighted least‐squares fitting of potassium (K), U, thorium (Th), and radon component spectra to the observed spectra. Both the spectral‐ratio and full‐spectrum methods are adequately calibrated through the estimation of component spectra from calibration experiments on the ground using radioactive calibration sources and wood to simulate the attenuation of gamma rays by air. The simulated heights used in these calibrations must be mapped onto real heights through calibration flights over an airborne calibration range. The spectral‐ratio method is also adequately calibrated using a heuristic calibration procedure. An iterative minimization method is used to find the optimum values of the calibration constants such that the radon background over suitable calibration lines is best removed.

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Gonçalves, Geraldo, Paula Coelho, Ricardo Schiavon, and Christopher Usher. "How well can we determine ages and chemical abundances from spectral fitting of integrated light spectra?" Monthly Notices of the Royal Astronomical Society 499, no. 2 (October 5, 2020): 2327–39. http://dx.doi.org/10.1093/mnras/staa3051.

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ABSTRACT The pixel-to-pixel spectral fitting technique is often used in studies of stellar populations. It enables the user to infer several parameters from integrated light spectra such as ages and chemical abundances. In this paper, we examine the question of how the inferred parameters change with the choice of wavelength range used. We have employed two different libraries of integrated light spectra of globular clusters (GCs) from the literature and fitted them to stellar population models using the code Starlight. We performed tests using different regions of the spectra to infer reddening, ages, [Fe/H], and [α/Fe]. Comparing our results to age values obtained from isochrone fitting and chemical abundances from high-resolution spectroscopy, we find that: (1) the inferred parameters change with the wavelength range used; (2) the method in general retrieves good reddening estimates, specially when a wider wavelength range is fitted; (3) the ideal spectral regions for determination of age, [Fe/H], and [α/Fe] are 4170–5540, 5280–7020, and 4828–5364 Å, respectively; (4) the retrieved age values for old metal-poor objects can be several Gyr younger than those resulting from isochrone fitting. We conclude that, depending on the parameter of interest and the accuracy requirements, fitting the largest possible wavelength range may not necessarily be the best strategy.

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Wang, Di, Tao Han, Huang-He Qian, Zhi-Yi Liu, and Zhi-Hua Ding. "An absolute wavenumber calibration method based on characteristic spectral line and constrained fitting phase." Acta Physica Sinica 71, no. 21 (2022): 214203. http://dx.doi.org/10.7498/aps.71.20220314.

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Spectral-domain optical coherence tomography (SD-OCT) systems generally have nonlinear sampling problems in wavenumber domain. In order to realize the precise positioning of the discrete interfaces and the high-quality reconstruction of OCT images under conventional fast Fourier transform, it is necessary to solve the precise calibration problem of the absolute wavenumber of the discrete sampling points in the spectrometer. In this work, an absolute wavenumber calibration method is proposed based on the absolute phase of the characteristic spectral line and the constraint polynomial fitting phase under precise optical path difference. In the sample arm of the SD-OCT system, the metal gauges with precise thickness difference are used to obtain the absolute phase value of the characteristic spectral line, and the phase wrapping times corresponding to the characteristic spectral line are further accurately solved. Thus, this method overcomes the 2π ambiguity of spectral phase in conventional interferometric phase methods. At the same time, combined with the polynomial fitting phase of the high signal-to-noise ratio region under window constraint, the accurate calibration of the absolute wavenumber of each sampling point is realized. Finally, comprehensive comparison between the proposed method and the traditional resampling method in terms of discrete interface positioning, axial resolution and image reconstruction quality verifies the significant advantages of this method.

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Ferry, A., and P. Jacobsson. "Curve Fitting and Deconvolution of Instrumental Broadening: A Simulated Annealing Approach." Applied Spectroscopy 49, no. 3 (March 1995): 273–78. http://dx.doi.org/10.1366/0003702953963643.

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A curve-fitting procedure based on the simulated annealing algorithm has been developed for the analysis of spectral Raman data. By the inclusion of a priori information about the instrumental broadening in the definition of the cost function that is minimized, effects of the finite instrumental resolution are eliminated from the resulting fit. The ability of the method to reproduce original band shapes is tested on synthesized spectra and FT-Raman spectra of diamond recorded at different resolutions with different apodization functions. The procedure yields the global optimum of the fitted parameters and is easily implemented on a personal computer.

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Wu, X., X. Zhang, and H. Lin. "SUPERPIXEL BASED FACTOR ANALYSIS AND TARGET TRANSFORMATION METHOD FOR MARTIAN MINERALS DETECTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1901–6. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1901-2018.

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The Factor analysis and target transformation (FATT) is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES) and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM) hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC) algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.

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Chadney, Joshua M., and Daniel K. Whiter. "Neutral temperature and atmospheric water vapour retrieval from spectral fitting of auroral and airglow emissions." Geoscientific Instrumentation, Methods and Data Systems 7, no. 4 (November 30, 2018): 317–29. http://dx.doi.org/10.5194/gi-7-317-2018.

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Abstract. We have developed a spectral fitting method to retrieve upper atmospheric parameters at multiple altitudes simultaneously during times of aurora, allowing us to measure neutral temperatures and column densities of water vapour. We use the method to separate airglow OH emissions from auroral O+ and N2 in observations between 725 and 740 nm using the High Throughput Imaging Echelle Spectrograph (HiTIES) located on Svalbard. In this paper, we describe our new method and show the results of Monte Carlo simulations using synthetic spectra which demonstrate the validity of the spectral fitting method and provide an indication of uncertainties on the retrieval of each atmospheric parameter. We show that the method allows for the retrieval of OH temperatures with an uncertainty of 6 % when contamination by N2 emission is small. N2 temperatures can be retrieved with uncertainties down to 3 %–5 % when N2 emission intensity is high. We can determine the intensity ratio between the O+ doublets at 732 and 733 nm (which is a function of temperature) with an uncertainty of 5 %.

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Liu, Lijia, Hua Ma, Zhendong Shi, Jinxi Bai, and lin Zhang. "A Real-Time Peak Extraction Algorithm for Dynamic Displacement Measurement Based on Spectral Confocal Microscopy." Journal of Physics: Conference Series 2112, no. 1 (November 1, 2021): 012015. http://dx.doi.org/10.1088/1742-6596/2112/1/012015.

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Abstract Spectral confocal is widely used in various fields such as topography detection, roughness measurement, thickness measurement, for its advantages ability in displacement measurement. Developed from confocal microscopy, the spectral confocal microscopy greatly improves the efficiency of displacement measurement because there is no need for longitudinal scanning, In other words, we need to obtain the wavelength information corresponding to the peak point of the spectral signal, which is called peak abscissa but not the peak value. Therefore, Accurate and efficient peak abscissa calculation algorithm occupies an important position in displacement monitoring based on spectral confocal. However, the existing methods are too complex to apply to real-time dynamic online detection, for they usually focus on determining the peak value by means of curve fitting and peak extraction. In this paper, we proposed an efficient and accurate peak abscissa calculation method by shifting, difference, linear fitting, zero point and peak abscissa calculation (SDLZ). Compared with the Gaussian fitting method, the results demonstrate that the SDLZ can greatly improve efficiency, can be applied to field programmable gate array microcontrollers, with high measurement accuracy, providing key solutions for equipment needs.

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Lu, Ning, Yanheng Zhang, and Wei Qiu. "Comparison and Selection of Data Processing Methods for the Application of Cr3+ Photoluminescence Piezospectroscopy to Thermal Barrier Coatings." Coatings 11, no. 2 (February 4, 2021): 181. http://dx.doi.org/10.3390/coatings11020181.

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Thermal barrier coatings (TBCs) are an indispensable part of the blades used in aeroengines. Under a high-temperature service environment, the thermal oxidation stress at the interface is the main cause of thermal barrier failure. Cr3+ photoluminescence piezospectroscopy has been successfully used to analyze the thermal oxidation stress of TBCs, but systematic and quantitative analysis results for use in data processing are still lacking, especially with respect to the identification of peak positions. The processing methods used to fit spectral data were studied in this work to accurately characterize TBC thermal oxidation stress using Cr3+ photoluminescence spectroscopy. Both physical and numerical experiments were carried out, where Cr3+ photoluminescence spectra were detected from alumina ceramic samples under step-by-step uniaxial loading, and the simulated spectra were numerically deduced from the measured spectral data. Then, the peak shifts were obtained by fitting all spectral data by using Lorentzian, Gaussian and Psd-Voigt functions. By comparing the fitting results and then discussing the generation mechanism, the Lorentzian function—not the Psd-Voigt function that is most widely utilized—was regarded as the most applicable method for the application of Cr3+ photoluminescence piezospectroscopy to TBCs because of its sufficient sensitivity, stability and confidence for quantitative stress analysis.

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Mossé, Caroline, Paul Génésio, Nelly Bonifaci, and Annette Calisti. "A New Procedure to Determine the Plasma Parameters from a Genetic Algorithm Coupled with the Spectral Line-Shape Code PPP." Atoms 6, no. 4 (September 26, 2018): 55. http://dx.doi.org/10.3390/atoms6040055.

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A method of analysis of experimental spectra for obtaining the plasma parameters is presented and discussed. Based on the coupling of the spectral line-shape code PPP with the genetic algorithm PIKAIA, the proposed method is inspired by natural selection mechanisms resulting in the development of basic genetic operators. The spectra analysis is performed by fitting experimental spectra with synthetic spectral line profiles obtained by using theoretical models and a set of plasma parameters, such as its temperature and electron density. In the present paper, the diagnostic procedure based on a genetic algorithm coupled with the PPP code has been used for the analysis of both hydrogen Balmer-β and He I 492.2 nm lines in the helium plasma created by corona discharge. The broadening of these spectral lines due to the Stark effect has been considered, together with the Van der Waals and instrumental broadening.

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Foschino, S., O. Berné, and C. Joblin. "Learning mid-IR emission spectra of polycyclic aromatic hydrocarbon populations from observations." Astronomy & Astrophysics 632 (December 2019): A84. http://dx.doi.org/10.1051/0004-6361/201935085.

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Context. The James Webb Space Telescope (JWST) will deliver an unprecedented quantity of high-quality spectral data over the 0.6−28 μm range. It will combine sensitivity, spectral resolution, and spatial resolution. Specific tools are required to provide efficient scientific analysis of such large data sets. Aims. Our aim is to illustrate the potential of unsupervised learning methods to get insights into chemical variations in the populations that carry the aromatic infrared bands (AIBs), more specifically polycyclic aromatic hydrocarbon (PAH) species and carbonaceous very small grains (VSGs). Methods. We present a method based on linear fitting and blind signal separation (BSS) for extracting representative spectra for a spectral data set. The method is fast and robust, which ensures its applicability to JWST spectral cubes. We tested this method on a sample of ISO-SWS data, which resemble most closely the JWST spectra in terms of spectral resolution and coverage. Results. Four representative spectra were extracted. Their main characteristics appear consistent with previous studies with populations dominated by cationic PAHs, neutral PAHs, evaporating VSGs, and large ionized PAHs, known as the PAHx population. In addition, the 3 μm range, which is considered here for the first time in a BSS method, reveals the presence of aliphatics connected to neutral PAHs. Each representative spectrum is found to carry second-order spectral signatures (e.g., small bands), which are connected with the underlying chemical diversity of populations. However, the precise attribution of theses signatures remains limited by the combined small size and heterogeneity of the sample of astronomical spectra available in this study. Conclusions. The upcoming JWST data will allow us to overcome this limitation. The large data sets of hyperspectral images provided by JWST analysed with the proposed method, which is fast and robust, will open promising perspectives for our understanding of the chemical evolution of the AIB carriers.

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Liu, Yu, Ya Yuan Zhang, Min Huang, and Xian Yao Wu. "A Kind of Color Calculation Method of Light Beam Hologram Papers Presswork." Applied Mechanics and Materials 731 (January 2015): 103–7. http://dx.doi.org/10.4028/www.scientific.net/amm.731.103.

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By using printability tester for printing on ordinary white cardboard and light beam hologram paper, measuring spectral information and chrominance information of the two samples, and then perform spectral fitting by analyses their color characteristics, The aim of this research was to propose one method for color calculation of printing on light beam hologram papers, according to the color information of ordinary white cardboard.

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Han, Xin, Shun Yang, Jingshan Bo, Chaoyu Chang, Mei Guo, and Yimeng Cai. "A New Method for the Calibration of Site-Related Response Spectra." Advances in Civil Engineering 2022 (July 30, 2022): 1–13. http://dx.doi.org/10.1155/2022/1713482.

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The calibration of response spectra is an important issue that needs further research in engineering earthquake resistance. This paper proposes an improved calibration method for site-related response spectra. The seismic acceleration response spectra are statistically analyzed in the random period bands in the form of regression analysis, and the fitting indices in each frequency band under 11 different functions are given. Accordingly, the best fitting function for each period band is determined. Combined with a genetic algorithm, the control parameters of the seismic acceleration response spectrum are calibrated according to the determined new design spectral shape. After comparing the calibration results with the proposed piecewise results, a new calibration model of the three-section curve expression is proposed by improving the piecewise standard until the calibration results are identical to the proposed period point. The accuracy of the proposed calibration method is validated against the other four available methods using Qian’a earthquake records and actual engineering examples. The research results show that the site-related response spectrum calibration method given in this paper objectively reflects the spectrum characteristics of the site-related response spectrum. The proposed method may have a certain reference value for the calibration of the site-related response spectrum.

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Silalahi, Divo Dharma, Habshah Midi, Jayanthi Arasan, Mohd Shafie Mustafa, and Jean-Pierre Caliman. "Automated Fitting Process Using Robust Reliable Weighted Average on Near Infrared Spectral Data Analysis." Symmetry 12, no. 12 (December 17, 2020): 2099. http://dx.doi.org/10.3390/sym12122099.

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With the complexity of Near Infrared (NIR) spectral data, the selection of the optimal number of Partial Least Squares (PLS) components in the fitted Partial Least Squares Regression (PLSR) model is very important. Selecting a small number of PLS components leads to under fitting, whereas selecting a large number of PLS components results in over fitting. Several methods exist in the selection procedure, and each yields a different result. However, so far no one has been able to determine the more superior method. In addition, the current methods are susceptible to the presence of outliers and High Leverage Points (HLP) in a dataset. In this study, a new automated fitting process method on PLSR model is introduced. The method is called the Robust Reliable Weighted Average—PLS (RRWA-PLS), and it is less sensitive to the optimum number of PLS components. The RRWA-PLS uses the weighted average strategy from multiple PLSR models generated by the different complexities of the PLS components. The method assigns robust procedures in the weighing schemes as an improvement to the existing Weighted Average—PLS (WA-PLS) method. The weighing schemes in the proposed method are resistant to outliers and HLP and thus, preserve the contribution of the most relevant variables in the fitted model. The evaluation was done by utilizing artificial data with the Monte Carlo simulation and NIR spectral data of oil palm (Elaeis guineensis Jacq.) fruit mesocarp. Based on the results, the method claims to have shown its superiority in the improvement of the weight and variable selection procedures in the WA-PLS. It is also resistant to the influence of outliers and HLP in the dataset. The RRWA-PLS method provides a promising robust solution for the automated fitting process in the PLSR model as unlike the classical PLS, it does not require the selection of an optimal number of PLS components.

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Zhou, Huailai, Yuanjun Wang, Tengfei Lin, Fangyu Li, and Kurt J. Marfurt. "Value of nonstationary wavelet spectral balancing in mapping a faulted fluvial system, Bohai Gulf, China." Interpretation 3, no. 3 (August 1, 2015): SS1—SS13. http://dx.doi.org/10.1190/int-2014-0128.1.

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Seismic data with enhanced resolution allow interpreters to effectively delineate and interpret architectural components of stratigraphically thin geologic features. We used a recently developed time-frequency domain deconvolution method to spectrally balance nonstationary seismic data. The method was based on polynomial fitting of seismic wavelet magnitude spectra. The deconvolution increased the spectral bandwidth but did not amplify random noise. We compared our new spectral modeling algorithm with existing time-variant spectral-whitening and inverse [Formula: see text]-filtering algorithms using a 3D offshore survey acquired over Bohai Gulf, China. We mapped these improvements spatially using a suite of 3D volumetric coherence, energy, curvature, and frequency attributes. The resulting images displayed improved lateral resolution of channel edges and fault edges with few, if any artifacts associated with amplification of random noise.

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Han, Yunkun, Zhanwen Han, and Lulu Fan. "Bayesian discrimination of the panchromatic spectral energy distribution modelings of galaxies." Proceedings of the International Astronomical Union 15, S341 (November 2019): 143–46. http://dx.doi.org/10.1017/s1743921319002746.

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AbstractFitting the multi-wavelength spectral energy distributions (SEDs) of galaxies is a widely used technique to extract information about the physical properties of galaxies. However, a major difficulty lies in the numerous uncertainties regarding almost all ingredients of the SED modeling of galaxies. The Bayesian methods provide a consistent conceptual basis for dealing with the problem of inference with many uncertainties. While the Bayesian parameter estimation method have become quite popular in the field of SED fitting of galaxies, the Bayesian model comparison method, which is based on the same Bayes’ rule, is still not widely used in this field. With the application of Bayesian model comparison method in a series of papers, we show that the results obtained with Bayesian model comparison are understandable in the context of stellar/galaxy physics. These results indicate that Bayesian model comparison is a reliable and very powerful method for the SED fitting of galaxies.

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Soto, Marcelo A., Alin Jderu, Dorel Dorobantu, Marius Enachescu, and Dominik Ziegler. "High-Order Polynomial Fitting Assistance for Fast Double-Peak Finding in Brillouin-Distributed Sensing." Sensors 21, no. 1 (December 30, 2020): 187. http://dx.doi.org/10.3390/s21010187.

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A high-order polynomial fitting method is proposed to accelerate the computation of double-Gaussian fitting in the retrieval of the Brillouin frequency shifts (BFS) in optical fibers showing two local Brillouin peaks. The method is experimentally validated in a distributed Brillouin sensor under different signal-to noise ratios and realistic spectral scenarios. Results verify that a sixth-order polynomial fitting can provide a reliable initial estimation of the dual local BFS values, which can be subsequently used as initial parameters of a nonlinear double-Gaussian fitting. The method demonstrates a 4.9-fold reduction in the number of iterations required by double-Gaussian fitting and a 3.4-fold improvement in processing time.

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Mohammed, Redwan Abdo A., Daniel Schäle, Christoph Hornberger, and Steffen Emmert. "Detecting Signatures in Hyperspectral Image Data of Wounds: A Compound Model of Self- Organizing Map and Least Square Fitting." Current Directions in Biomedical Engineering 4, no. 1 (September 1, 2018): 419–22. http://dx.doi.org/10.1515/cdbme-2018-0100.

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AbstractThe purpose of this study is to develop a method to discriminate spectral signatures in wound tissue. We have collected a training set of the intensity of the remitted light for different types of wound tissue from different patients using a TIVITA™ tissue camera. We used a neural network technique (self-organizing map) to group areas with the same spectral properties together. The results of this work indicates that neural network models are capable of finding clusters of closely related hyperspectral signatures in wound tissue, and thus can be used as a powerful tool to reach the anticipated classification. Moreover, we used a least square method to fit literature spectra (i.e. oxygenated haemoglobin (O2Hb), deoxygenated haemoglobin (HHb), water and fat) to the learned spectral classes. This procedure enables us to label each spectral class with the corresponding absorbance properties for the different absorbance of interest (i.e. O2Hb, HHb, water and fat). The calculated parameters of a testing set were consistent with the expected behaviour and show a good agreement with the results of a second algorithm which is used in the TIVITA™ tissue camera.

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Xiao, Tian Yin. "Power Spectral Density Model of Torsional Dynamic Wind Loads on Tall Buildings." Applied Mechanics and Materials 164 (April 2012): 433–36. http://dx.doi.org/10.4028/www.scientific.net/amm.164.433.

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9 models of tall buildings with different rectangular cross-sections are tested in a wind tunnel. After processing and analyzing the measured data of fluctuating pressure on the models, the effects of models’height, aspect ratio, side ratio on the power spectra of torsional wind loads are studied. New formulas of power spectral density of torsional wind loads are proposed by curve fitting method. The applicability of the formulas has been verified by the results from the wind tunnel test.

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Flor-Torres, L. M., R. Coziol, K. P. Schröder, D. Jack, J. H. M. M. Schmitt, and S. Blanco-Cuaresma. "CONNECTING THE FORMATION OF STARS AND PLANETS. I – SPECTROSCOPIC CHARACTERIZATION OF HOST STARS WITH TIGRE." Revista Mexicana de Astronomía y Astrofísica 57, no. 1 (April 1, 2021): 199–216. http://dx.doi.org/10.22201/ia.01851101p.2021.57.01.15.

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In search for a connection between the formation of stars and the formation of planets, a new semi-automatic spectral analysis method using iSpec was developed for the TIGRE telescope installed in Guanajuato, Mexico. TIGRE is a 1.2m robotic telescope, equipped with an Echelle spectrograph (HEROS), with a resolution R ≃ 20000. iSpec is a synthetic spectral fitting program for stars that allows to determine in an homogeneous way their fundamental parameters: effective temperature, Teff, surface gravity, log g, metallicities, [M/H] and [Fe/H], and rotational velocity, V sin i. In this first article we test our method by analysing the spectra of 46 stars, hosts of exoplanets, obtained with the TIGRE.

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Ozaki, Yukihiro, Slobodan Šašić, and Jian Hui Jiang. "How Can We Unravel Complicated near Infrared Spectra?—Recent Progress in Spectral Analysis Methods for Resolution Enhancement and Band Assignments in the near Infrared Region." Journal of Near Infrared Spectroscopy 9, no. 2 (March 2001): 63–95. http://dx.doi.org/10.1255/jnirs.295.

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This review paper reports recent progress in spectral analysis methods for resolution enhancement and band assignments in the near infrared (NIR) region. Spectra in the NIR region are inherently rich with information on the physical and chemical properties of molecules. However, it is not always straightforward to analyse the spectra because an NIR spectrum consists of a number of overlapped bands due to overtones and combination modes. An NIR spectrum may be analysed by conventional spectral analysis methods, chemometrics or two-dimensional correlation spectroscopy. The following conventional methods are currently utilised to analyse NIR spectra: (a) derivatives, (b) difference spectroscopy, (c) Fourier self-deconvolution and (d) curve fitting. The derivative method is powerful in separating superimposed bands and correcting for a baseline slope. Conventional experimental methods for spectral analysis, such as isotope exchange and measurement of polarisation spectra, are also valid in the NIR region. Chemometrics is very useful for extracting information from NIR spectra. Among a variety of chemometrics methods, multiple linear regression, principal component analysis, principal component regression and partial least squares regression are most often used for qualitative and quantitative analysis. Recently, chemometrics has been used for resolution enhancement of NIR spectra. Particularly, loadings plots or regression coefficients are useful for separating overlapped bands and for making band assignments. Notable recent advances in the analysis of NIR spectroscopy are the development or introduction of new spectral analysis methods such as two-dimensional (2D) correlation spectroscopy and self-modelling curve resolution methods (SMCR). 2D correlation analysis enables enhancement of apparent spectral resolution by spreading spectral peaks over a second dimension. SMCR allows one to resolve the experimental matrix into concentration profiles and pure spectra of the involved species without prior knowledge of any of these features.

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Lacroix, Elodie, Jean Cauzid, Yoram Teitler, and Michel Cathelineau. "Near real-time management of spectral interferences with portable X-ray fluorescence spectrometers: application to Sc quantification in nickeliferous laterite ores." Geochemistry: Exploration, Environment, Analysis 21, no. 3 (July 23, 2021): geochem2021–015. http://dx.doi.org/10.1144/geochem2021-015.

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Since the development of portable X-ray fluorescence (pXRF) spectrometers, few studies have been conducted on the influence of spectral interferences between chemical elements. This study aims to improve the management of these interferences to obtain more reliable geochemical analyses. We specifically investigate Ca-related interferences on Sc analysis for the case of Ni-rich laterite samples using the Niton XL3t GOLDD + pXRF analyser. Three quantification methods were tested on 59 pelletized samples using the ‘Soil’ mode. The first, named ‘Manufacturer’, represents the elemental quantification directly provided by the device based on regions of interest and multilinear corrections of spectral interferences configured during the spectrometer design. The second, the ‘20 Cu’ method, is based on spectral fitting using the PyMCA software. The third, the ‘18 Fe’ method, combines spectral fitting with modified experimental conditions. For each, a quantification methodology was developed, establishing (i) Ca and Sc calibration lines and (ii) Ca/Sc threshold values delimiting fields of ‘reliable’, ‘to be confirmed’ and ‘unreliable’ measurements. The ‘20 Cu’ and ‘18 Fe’ methods greatly extend the ‘reliable measurements’ field concerning the Ca/Sc ratio compared to the ‘Manufacturer’ method. The ‘18 Fe’ method was also found to provide the most negligible measurement dispersion.Supplementary material: Figures A–F and Tables A and B are available at https://doi.org/10.6084/m9.figshare.c.5511838

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Zdziarski, Andrzej A., Michał Szanecki, Juri Poutanen, Marek Gierliński, and Paweł Biernacki. "Spectral and temporal properties of Compton scattering by mildly relativistic thermal electrons." Monthly Notices of the Royal Astronomical Society 492, no. 4 (January 17, 2020): 5234–46. http://dx.doi.org/10.1093/mnras/staa159.

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ABSTRACT We have obtained new solutions and methods for the process of thermal Comptonization. We modify the solution to the kinetic equation of Sunyaev and Titarchuk to allow its application up to mildly relativistic electron temperatures and optical depths $\gtrsim {1}$. The solution can be used for spectral fitting of X-ray spectra from astrophysical sources. We also have developed an accurate Monte Carlo method for calculating spectra and timing properties of thermal Comptonization sources. The accuracy of our kinetic equation solution is verified by comparison with the Monte Carlo results. We also compare our results with those of other publicly available methods. Furthermore, based on our Monte Carlo code, we present distributions of the photon emission times and the evolution of the average photon energy for both up and down scattering.

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Matviychuk, Yevgen, Ellen Steimers, Erik von Harbou, and Daniel J. Holland. "Improving the accuracy of model-based quantitative nuclear magnetic resonance." Magnetic Resonance 1, no. 2 (July 2, 2020): 141–53. http://dx.doi.org/10.5194/mr-1-141-2020.

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Abstract. Low spectral resolution and extensive peak overlap are the common challenges that preclude quantitative analysis of nuclear magnetic resonance (NMR) data with the established peak integration method. While numerous model-based approaches overcome these obstacles and enable quantification, they intrinsically rely on rigid assumptions about functional forms for peaks, which are often insufficient to account for all unforeseen imperfections in experimental data. Indeed, even in spectra with well-separated peaks whose integration is possible, model-based methods often achieve suboptimal results, which in turn raises the question of their validity for more challenging datasets. We address this problem with a simple model adjustment procedure, which draws its inspiration directly from the peak integration approach that is almost invariant to lineshape deviations. Specifically, we assume that the number of mixture components along with their ideal spectral responses are known; we then aim to recover all useful signals left in the residual after model fitting and use it to adjust the intensity estimates of modelled peaks. We propose an alternative objective function, which we found particularly effective for correcting imperfect phasing of the data – a critical step in the processing pipeline. Application of our method to the analysis of experimental data shows the accuracy improvement of 20 %–40 % compared to the simple least-squares model fitting.

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Mao, Ning, Baoan Song, Lei Pan, Xinli Liu, Changgui Lin, Peiqing Zhang, Xiang Shen, and Shixun Dai. "Spectral fitting method for obtaining the refractive index and thickness of chalcogenide films." Optics Express 29, no. 18 (August 26, 2021): 29329. http://dx.doi.org/10.1364/oe.438391.

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Mokiem, M. R., A. de Koter, J. Puls, A. Herrero, F. Najarro, and M. R. Villamariz. "Spectral analysis of early-type stars using a genetic algorithm based fitting method." Astronomy & Astrophysics 441, no. 2 (September 19, 2005): 711–33. http://dx.doi.org/10.1051/0004-6361:20053522.

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Wen, Yu-Che, Senfar Wen, Long Hsu, and Sien Chi. "Spectral Reflectance Recovery from the Quadcolor Camera Signals Using the Interpolation and Weighted Principal Component Analysis Methods." Sensors 22, no. 16 (August 21, 2022): 6288. http://dx.doi.org/10.3390/s22166288.

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The recovery of surface spectral reflectance using the quadcolor camera was numerically studied. Assume that the RGB channels of the quadcolor camera are the same as the Nikon D5100 tricolor camera. The spectral sensitivity of the fourth signal channel was tailored using a color filter. Munsell color chips were used as reflective surfaces. When the interpolation method or the weighted principal component analysis (wPCA) method is used to reconstruct spectra, using the quadcolor camera can effectively reduce the mean spectral error of the test samples compared to using the tricolor camera. Except for computation time, the interpolation method outperforms the wPCA method in spectrum reconstruction. A long-pass optical filter can be applied to the fourth channel for reducing the mean spectral error. A short-pass optical filter can be applied to the fourth channel for reducing the mean color difference, but the mean spectral error will be larger. Due to the small color difference, the quadcolor camera using an optimized short-pass filter may be suitable as an imaging colorimeter. It was found that an empirical design rule to keep the color difference small is to reduce the error in fitting the color-matching functions using the camera spectral sensitivity functions.

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Małek, K., V. Buat, Y. Roehlly, D. Burgarella, P. D. Hurley, R. Shirley, K. Duncan, et al. "HELP: modelling the spectral energy distributions of Herschel detected galaxies in the ELAIS N1 field." Astronomy & Astrophysics 620 (November 30, 2018): A50. http://dx.doi.org/10.1051/0004-6361/201833131.

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Aims. The Herschel Extragalactic Legacy Project (HELP) focuses on the data from ESA’s Herschel mission, which covered over 1300 deg2 and is preparing to publish a multi-wavelength catalogue of millions of objects. Our main goal is to find the best approach to simultaneously fitting spectral energy distributions (SEDs) of millions of galaxies across a wide redshift range to obtain homogeneous estimates of the main physical parameters of detected infrared (IR) galaxies. Methods. We perform SED fitting on the ultraviolet(UV)/near-infrared(NIR) to far-infrared(FIR) emission of 42 047 galaxies from the pilot HELP field: ELAIS N1. To do this we use the latest release of CIGALE, a galaxy SED fitting code relying on energy balance, to deliver the main physical parameters such as stellar mass, star formation rate, and dust luminosity. We implement additional quality criteria to the fits by calculating χ2 values for the stellar and dust part of the spectra independently. These criteria allow us to identify the best fits and to identify peculiar galaxies. We perform the SED fitting of ELAIS N1 galaxies by assuming three different dust attenuation laws separately allowing us to test the impact of the assumed law on estimated physical parameters. Results. We implemented two additional quality value checks for the SED fitting method based on stellar mass estimation and energy budget. This method allows us to identify possible objects with incorrect matching in the catalogue and peculiar galaxies; we found 351 possible candidates of lensed galaxies using two complementary χ2s criteria (stellar and infrared χ2s) and photometric redshifts calculated for the IR part of the spectrum only. We find that the attenuation law has an important impact on the stellar mass estimate (on average leading to disparities of a factor of two). We derive the relation between stellar mass estimates obtained by three different attenuation laws and we find the best recipe for our sample. We also make independent estimates of the total dust luminosity parameter from stellar emission by fitting the galaxies with and without IR data separately.

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Yu, Tian-You, Ricardo Reinoso Rondinel, and Robert D. Palmer. "Investigation of Non-Gaussian Doppler Spectra Observed by Weather Radar in a Tornadic Supercell." Journal of Atmospheric and Oceanic Technology 26, no. 3 (March 1, 2009): 444–61. http://dx.doi.org/10.1175/2008jtecha1124.1.

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Abstract Radar Doppler spectra that deviate from a Gaussian shape were observed from a tornadic supercell on 10 May 2003, exhibiting features such as a dual peak, flat top, and wide skirt in the nontornadic region. Motivated by these observations, a spectral model of a mixture of two Gaussian components, each defined by its three spectral moments, is introduced to characterize different degrees of deviation from Gaussian shape. In the standard autocovariance method, a Gaussian spectrum is assumed and biases in velocity and spectrum width estimates may result if this assumption is violated. The impact of non-Gaussian weather spectra on these biases is formulated and quantified in theory and, consequently, verified using four experiments of numerical simulations. Those non-Gaussian spectra from the south region of the supercell are further examined and a nonlinear fitting algorithm is proposed to estimate the six spectral moments and compare to those obtained from the autocovariance method. It is shown that the dual-Gaussian model can better represent observed spectra for those cases. The authors’ analysis suggests that vertical shear may be responsible for the flat-top or the dual-peak spectra in the lower elevation of 0.5° and their transition to the single-peak and wide-skirt spectra in the next elevation scan of 1.5°.

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Лигер, В. В., В. Р. Мироненко, Ю. А. Курицын, and М. А. Большов. "Диагностика горячих зон методом абсорбционной спектроскопии с диодными лазерами (обзор)." Журнал технической физики 127, no. 7 (2019): 55. http://dx.doi.org/10.21883/os.2019.07.47931.86-19.

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AbstractA review of the works that we have been carried in the last 5 years on the use of the method of absorption spectroscopy with diode lasers for the diagnosis of hot zone parameters is given. A spectrometer with two lasers operating in different spectral ranges with sufficiently strong absorption lines has been developed for the case of high pressures and gas temperature. The results of the search for optimal lines in different spectral ranges have been presented. The results of laboratory measurements and tests at the experimental power stand at TSAGI Named after Prof. N.E. Zhukovsky have been presented. Approaches to determining the maximum temperature for spatially inhomogeneous hot zones have been discussed. The method of difference spectra and method of fitting the experimental spectrum with the sum of one-temperature spectra have been proposed. The efficiency of the proposed processing algorithms for specific types of hot zones has been shown experimentally.

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Lin, Shuyuan, Guobao Xiao, Yan Yan, David Suter, and Hanzi Wang. "Hypergraph Optimization for Multi-Structural Geometric Model Fitting." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8730–37. http://dx.doi.org/10.1609/aaai.v33i01.33018730.

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Recently, some hypergraph-based methods have been proposed to deal with the problem of model fitting in computer vision, mainly due to the superior capability of hypergraph to represent the complex relationship between data points. However, a hypergraph becomes extremely complicated when the input data include a large number of data points (usually contaminated with noises and outliers), which will significantly increase the computational burden. In order to overcome the above problem, we propose a novel hypergraph optimization based model fitting (HOMF) method to construct a simple but effective hypergraph. Specifically, HOMF includes two main parts: an adaptive inlier estimation algorithm for vertex optimization and an iterative hyperedge optimization algorithm for hyperedge optimization. The proposed method is highly efficient, and it can obtain accurate model fitting results within a few iterations. Moreover, HOMF can then directly apply spectral clustering, to achieve good fitting performance. Extensive experimental results show that HOMF outperforms several state-of-the-art model fitting methods on both synthetic data and real images, especially in sampling efficiency and in handling data with severe outliers.

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Chen, Li, and Marc Garland. "Band Centers and Track Finding for Large Two-Dimensional Infrared Spectroscopic Arrays." Applied Spectroscopy 57, no. 3 (March 2003): 323–30. http://dx.doi.org/10.1366/000370203321558245.

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An efficient two-dimensional (2D) peak-finding algorithm is proposed to find peak maps that specify the peak centers of all bands in two-dimensional arrays of time-series infrared spectral data. The algorithm combines the second-derivative method with the intrinsic characteristics of 2D infrared reaction spectral data. Initially, the second-derivative method is used to detect all possible peak center positions, and then three criteria drawn from characteristics of 2D continuous spectral data are employed to filter peak positions. Four 2D peak maps are generated in a sequential order, with better and better approximations to the peak center positions being obtained in each. The 2D peak-finding algorithm has been successfully applied to both simulated spectra (to initially evaluate the algorithm) and then real 2D experimental spectra. The resulting peak maps exhibit very good estimates of the peak center positions. An ordering from the most significant to the least significant bands is obtained. The final peak maps can be used as starting parameters for various applications including the computationally intensive curve-fitting of time-series data.

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Journal articles on the topic 'Spectral fitting method'

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