Residual stress determination by blind hole drilling and local displacement mapping in aluminium alloy aerospace components by Sviatoslav Eleonsky, Vladimir Pisarev, Eugene Statnik, Alexey Salimon, Alexander Korsunsky

“…It can be concluded from the analysis of the problem that the formulae connecting the raw experimental data and to the sought residual stress component values lead to a well-posed inverse problem. This makes it possible to obtain estimations of the measurement uncertainty. …”
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Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution by Keivan Faghih Niresi, Chong-Yung Chi

“…This article considers the inverse problem under hyperspectral images (HSIs) denoising framework. …”
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A Proposed Bearing Load Identification Method to Uncertain Rotor Systems by Wengui Mao, Nannan Zhang, Dan Feng, Jianhua Li

“…The perturbation analysis method based on Taylor expansion is used to transform the problem of the bearing load identification involving in probability parameters into two kinds of certain inverse problem, namely, the bearing load identification combining the mean value of uncertain parameters with calculated transient response function and the sensitivity identification of bearing load to each probability parameter. …”
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A Radio-interferometric Imaging Method Based on the Wavelet Tight Frame by Xiaocheng Yang, Xiang You, Lin Wu, Jingye Yan, Feng Liu, Mingfeng Jiang, Junbao Zheng

“…Reconstructing the signal from measured visibilities in radio interferometry is an ill-posed inverse problem. In this paper, we present a novel radio-interferometric imaging method based on the wavelet tight frame aimed at efficiently obtaining an accurate solution. …”
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Inverse Modeling of Nonlinear Artificial Muscle Using Polynomial Parameterization and Particle Swarm Optimization by Mohd Azuwan Mat Dzahir, Shin-ichiroh Yamamoto

“…Even though an inverse modeling of PAM has limited application, it is important on certain control system implementation that requires the solution to the inverse problem. In this paper, the inverse modeling of PAM in the form of activation pressure was proposed. …”
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Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation by O. Lamminpää, J. Susiluoto, J. Hobbs, J. McDuffie, A. Braverman, H. Owhadi

“…The retrieval, or solving an inverse problem, requires substantial computational resources. …”
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Preliminary Results of Marine Electromagnetic Sounding with a Powerful, Remote Source in Kola Bay off the Barents Sea by Valery Grigoryev, Sergey Korotaev, Mikhail Kruglyakov, Darya Orekhova, Yury Scshors, Evgeniy Tereshchenko, Pavel Tereshchenko, Igor Trofimov

“…These preliminary results open the possibility of inverse problem solving with more reliable geological conclusions.…”
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Features of the Surface and Subsurface Waves Application for Ultrasonic Evaluation of Physicomechanical Properties of Solids. Part 2. Strenghtned Inhomogeneous Surface Layer by A. R. Baev, A. L Mayorov, N. V. Levkovich, M. V. Asadchaya

“…It is shown that the proposed approach is promising for solving the inverse problem of restoring the spatial distribution of hardness based on experimental data.The goniometric method was approbated to determine the dependence between amplitude-angle characteristics and depth of the surface steel layers hardened by high-frequency hardening and depth of hardened gray iron specimens layer – with chill. …”
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HDNLS: Hybrid Deep-Learning and Non-Linear Least Squares-Based Method for Fast Multi-Component T1ρ Mapping in the Knee Joint by Dilbag Singh, Ravinder R. Regatte, Marcelo V. W. Zibetti

“…HDNLS combines voxel-wise DL, trained with synthetic data, with a few iterations of NLS to accelerate the fitting process, thus eliminating the need for reference MRI data for training. Due to the inverse-problem nature of the parameter mapping, certain parameters in a specific model may be more sensitive to noise, such as the short component in the BE model. …”
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Cutting tool feed drive of wafer background milling machine by E. S. Gebel, A. Yu. Popov, I. N. Drozdov

“…In order to realize the required trapezoidal law of the output link speed change, the inverse problem of kinematics solved, numerical values of the instantaneous angular velocity of the input crank and pulse control signals to the servomotor obtained.…”
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MINIMIZATION OF RISK OF THE ERRONEOUS DECISION IN THE ASSESSMENT OF THE IMPORTANCE OF STATISTICAL RELATIONS OF TECHNICAL AND ECONOMIC INDICATORS OF THE OBJECTS OF ELECTRIC POWER SY... by E. M. Farhadzadeh, A. Z. Muradaliyev, Yu. Z. Farzaliyev, T. K. Rafiyeva, S. A. Abdullayeva

“…The novelty consists in the application of fiducial approach; the calculation of critical values are fulfilled with the aid of computer technologies of simulation of possible realizations of the correlation coefficients for the two assumptions, viz. technical and economic indicators of the independent and dependent; simulation is fulfilled with the method of solving the “inverse problem”, which enables the possible implementation of the correlation coefficients for the really dependent and independent samples of random variables at a given sample size; the developed algorithms and programs for calculation made it possible to obtain the critical values of correlation coefficients for independent and dependent samples; in conditions of the sameness of the consequences of erroneous decisions it is proposed to make a decision not based on critical value but based on the boundary values of the correlation coefficients that correspond to the minimum total risk of erroneous decisions; the exemplification of the recommendations application was made on example of technical and economic parameters of boilers of power units of 300 MWt. …”
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Method for assessing the theoretical characteristics of small axial hydraulic turbines by D. V. Mylkin, A. V. Volkov, B. M. Orakhelashvili, A. A. Druzhinin, V. Yu. Lyapin

“…Designing hydraulic turbines is a complex task that requires solving the inverse problem of hydrodynamics and finding the optimal shape of the flow path. …”
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Exploring parameter dependence of atomic minima with implicit differentiation by Ivan Maliyov, Petr Grigorev, Thomas D. Swinburne

“…Forward propagation of parameter variation is key for uncertainty quantification, whilst backpropagation has found application for emerging inverse problems such as fine-tuning or targeted design. …”
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Data Fusion for Electromagnetic and Electrical Resistive Tomography Based on Maximum Likelihood by Sven Nordebo, Mats Gustafsson, Therese Sjöden, Francesco Soldovieri

“…The statistical maximum likelihood criterion is closely linked to the additive Fisher information measure, and it facilitates an appropriate weighting of the measurement data which can be useful with multiphysics inverse problems. The Fisher information is particularly useful for inverse problems which can be linearized similar to the Born approximation. …”
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Computing the Fixed Points of Strictly Pseudocontractive Mappings by the Implicit and Explicit Iterations by Yeong-Cheng Liou

“…It is known that strictly pseudocontractive mappings have more powerful applications than nonexpansive mappings in solving inverse problems. In this paper, we devote to study computing the fixed points of strictly pseudocontractive mappings by the iterations. …”
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Nonlinear stochastic Markov processes and modeling uncertainty in populations by H.Thomas Banks, Shuhua Hu

“…Moreover, these alternate formulations lead to fast efficient calculations in inverse problems as well as in forward simulations. Here we derive a class of stochastic formulations for which such an alternate representation is readily found.…”
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The estimation of the effective reproductive number from disease outbreak data by Ariel Cintrón-Arias, Carlos Castillo-Chávez, Luís M. A. Bettencourt, Alun L. Lloyd, H. T. Banks

“…We use asymptotic statisticaltheories to derive the mean and variance of the limiting(Gaussian) sampling distribution and to perform post statisticalanalysis of the inverse problems. We illustrate the ideas andpitfalls (e.g., large condition numbers on the correspondingFisher information matrix) with both synthetic and influenzaincidence data sets.…”
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A General Result on the Mean Integrated Squared Error of the Hard Thresholding Wavelet Estimator under α-Mixing Dependence by Christophe Chesneau

“…Applications are given for two types of inverse problems: the deconvolution density estimation and the density estimation in a GARCH-type model, both improve existing results in this dependent context. …”
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An Optimally Generalized Steepest-Descent Algorithm for Solving Ill-Posed Linear Systems by Chein-Shan Liu

“…The optimally generalized steepest-descent algorithm (OGSDA) is proven to be convergent with very fast convergence speed, accurate and robust against noisy disturbance, which is confirmed by numerical tests of some well-known ill-posed linear problems and linear inverse problems.…”
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Total Variation Regularization Algorithms for Images Corrupted with Different Noise Models: A Review by Paul Rodríguez

“…Total Variation (TV) regularization has evolved from an image denoising method for images corrupted with Gaussian noise into a more general technique for inverse problems such as deblurring, blind deconvolution, and inpainting, which also encompasses the Impulse, Poisson, Speckle, and mixed noise models. …”
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