QuantitativeT2analysis: The effects of noise, regularization, and multivoxel approaches

2009 ◽  
pp. NA-NA ◽  
Author(s):  
Thorarin A. Bjarnason ◽  
Cheryl R. McCreary ◽  
Jeff F. Dunn ◽  
J. Ross Mitchell
Keyword(s):  
Noise Regularization

scholarly journals Noise regularization removes correlation artifacts in single-cell RNA-seq data preprocessing

2020 ◽  
Author(s):  
Ruoyu Zhang ◽  
Gurinder S. Atwal ◽  
Wei Keat Lim
Keyword(s):  
Single Cell ◽  
Gene Networks ◽  
Immune Cell ◽  
Data Preprocessing ◽  
Rna Seq ◽  
Imputation Methods ◽  
Individual Gene ◽  
Gene Associations ◽  
Cell Modules ◽  
Noise Regularization

AbstractWith the rapid advancement of single-cell RNA-seq (scRNA-seq) technology, many data preprocessing methods have been proposed to address numerous systematic errors and technical variabilities inherent in this technology. While these methods have been demonstrated to be effective in recovering individual gene expression, the suitability to the inference of gene-gene associations and subsequent gene networks reconstruction have not been systemically investigated. In this study, we benchmarked five representative scRNA-seq normalization/imputation methods on human cell atlas bone marrow data with respect to their impact on inferred gene-gene associations. Our results suggested that a considerable amount of spurious correlations was introduced during the data preprocessing steps due to over-smoothing of the raw data. We proposed a model-agnostic noise regularization method that can effectively eliminate the correlation artifacts. The noise regularized gene-gene correlations were further used to reconstruct gene co-expression network and successfully revealed several known immune cell modules.

Weighted-l1-method-noise regularization for image deblurring

2019 ◽  
Vol 157 ◽  
pp. 14-24 ◽  
Author(s):  
Chunyu Yang ◽  
Weiwei Wang ◽  
Xiangchu Feng ◽  
Xin Liu
Keyword(s):  
Image Deblurring ◽  
Method Noise ◽  
Noise Regularization

Reconstruction of Interior Sound Fields of Vibrating Shells with an Open Spherical Microphone Array

2016 ◽  
Vol 24 (04) ◽  
pp. 1650013 ◽  
Author(s):  
Minzong Li ◽  
Huancai Lu
Keyword(s):  
Cross Validation ◽  
Microphone Array ◽  
Sound Field ◽  
Reconstruction Error ◽  
Wave Number ◽  
Tikhonov Regularization Method ◽  
Sound Fields ◽  
Noise Regularization ◽  
Enclosed Space ◽  
The Impact

Spherical acoustic holography was utilized to reconstruct the interior sound field of an enclosed space with vibrating boundaries using an open spherical microphone array. The interior sound fields of vibrating shells, including a pulsating shell, a [Formula: see text]-axis oriented oscillating shell, a partially vibrating shell and a point-excited vibrating shell, were reconstructed, and numerical simulations were carried out to examine the impact of reconstruction parameters, the radius of the microphone array, the number of microphones, the distribution of microphones on the array surface, the wave number, the number of basis functions used, and the radius of the reconstruction surface on the accuracy of reconstruction. In order to minimize the error of reconstruction caused by a variety of factors and uncertainties, such as the measurement noise, regularization treatments were introduced into the process of reconstructing, to suppress the divergent trends of the reconstruction error along with the increase of the wave number and the increase of the radius of the reconstruction surface. Results showed that a Tikhonov regularization method with generalized cross validation (GCV) could yield the least error of reconstruction among the investigated regularization methods.

scholarly journals Noise regularization and computations for the 1-dimensional stochastic Allen–Cahn problem

2007 ◽  
pp. 1-30 ◽  
Author(s):  
Markos Katsoulakis ◽  
Georgios Kossioris ◽  
Omar Lakkis
Keyword(s):  
Noise Regularization

Laser stripe extraction in additive manufacturing based on spatiotemporal noise regularization

2020 ◽  
Vol 27 (6) ◽  
pp. 521-529
Author(s):  
Haotian Yu ◽  
Chongchong Peng ◽  
Zhuang Zhao ◽  
Yi Zhang
Keyword(s):  
Additive Manufacturing ◽  
Laser Stripe ◽  
Noise Regularization ◽  
Spatiotemporal Noise

Resolution recovery and noise regularization in nuclear cardiology

2016 ◽  
Vol 24 (1) ◽  
pp. 138-141 ◽  
Author(s):  
Olga James ◽  
Robert Pagnanelli ◽  
Salvador-Borges Neto
Keyword(s):  
Nuclear Cardiology ◽  
Resolution Recovery ◽  
Noise Regularization
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