Regularization by Intrinsic Plasticity and its Synergies with Recurrence for Random Projection Methods [PDF]
, 2012 Neumann K, Emmerich C, Steil JJ. Regularization by Intrinsic Plasticity and its Synergies with Recurrence for Random Projection Methods. Journal of Intelligent Learning Systems and Applications. 2012;4(3):230-246.Neural networks based on high-dimensional
Emmerich, Christian +2 more
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Stability estimate and regularization for a radially symmetric inverse heat conduction problem
Boundary Value Problems, 2017 This paper investigates a radially symmetric inverse heat conduction problem, which determines the internal surface temperature distribution of the hollow sphere from measured data at the fixed location inside it. This is an inverse and ill-posed problem.
Wei Cheng
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Journal of Harbin University of Science and Technology, 2020 Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature ...
SU Ziheng, CHEN Deyun, WANG Lili
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Constrained regularization methods for ozone profile retrieval from UV/VIS nadir spectrometers [PDF]
, 2009 In this paper we present several constrained regularization methods for ozone profile retrieval from UV/VIS nadir sounding instruments such as GOME, SCIAMACHY, OMI and GOME-2.
Doicu, Adrian +5 more
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A sequential regularization method for time-dependent incompressible Navier--Stokes equations [PDF]
, 1997 The objective of the paper is to present a method, called the sequential regularization method (SRM), for the nonstationary incompressible Navier--Stokes equations from the viewpoint of regularization of differential-algebraic equations (DAEs), and to ...
Lin, Ping
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On the regularization and optimization in quantum detector tomography [PDF]
, 2023 Quantum detector tomography (QDT) is a fundamental technique for calibrating quantum devices and performing quantum engineering tasks. In this paper, we utilize regularization to improve the QDT accuracy whenever the probe states are informationally ...
Hidehiro Yonezawa +13 more
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Regularized CNN Feature Hierarchy for Hyperspectral Image Classification
Remote Sensing, 2021 Convolutional Neural Networks (CNN) have been rigorously studied for Hyperspectral Image Classification (HSIC) and are known to be effective in exploiting joint spatial-spectral information with the expense of lower generalization performance and ...
Muhammad Ahmad +2 more
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Error Estimations for Total Variation Type Regularization
Mathematics, 2021 This paper provides several error estimations for total variation (TV) type regularization, which arises in a series of areas, for instance, signal and imaging processing, machine learning, etc.
Kuan Li, Chun Huang, Ziyang Yuan
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Estimation and Regularization Techniques for Regression Models with Multidimensional Prediction Functions [PDF]
, 2008 Boosting is one of the most important methods for fitting regression models and building prediction rules from high-dimensional data. A notable feature of boosting is that the technique has a built-in mechanism for shrinking coefficient estimates and
Potapov, Sergej +3 more
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Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Satellite soil moisture and vegetation optical depth [(VOD); related to the total vegetation water mass per unit area] are increasingly being used to study water relations in the soil-plant continuum across the globe.
Andrew Feldman +2 more
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