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Reconstruction of Mesoscale Precipitation Fields from Sparse Observations in Complex Terrain

Jürg Schmidli, Christoph Frei, Christoph Schär
2001 Journal of Climate  
The feasibility of a statistical reconstruction of mesoscale precipitation fields over complex topography from a sparse rain gauge network is examined.  ...  The statistical model is calibrated over a 15-yr period, and the reconstructed fields are evaluated for the remaining 5 yr of the period 1971-90.  ...  Department of the Environment Contract EPG 1/1/16) on behalf of the Climatic Research Unit, University of East Anglia.  ... 
doi:10.1175/1520-0442(2001)014<3289:rompff>2.0.co;2 fatcat:yiob3isyqjeoxpqhxot3ko2yty

Statistical structure of the large-scale fields of temperature and salinity in the Black Sea

A. B. Polonskii, I. G. Shokurova
2008 Physical Oceanography  
We study the dependence of the error of reconstruction of the fields by the method of optimal interpolation on the form of approximation of the correlation functions with regard for anisotropy.  ...  551.465(262.5) In order to reconstruct the large-scale temperature and salinity fields by the method of optimal interpolation of the archival data, we compute the correlation functions and analyze the  ...  In the case of reconstruction of large-scale structures for a sparse network, the analysis of the influence of anisotropy improves the results of reconstruction of the fields and enables us to get fields  ... 
doi:10.1007/s11110-008-9008-4 fatcat:5u3godwyrvhevjnxr5ke4ctgsq

The Critical Study of Mutual Coherence Properties on Compressive Sensing Framework for Sparse Reconstruction Performance: Compression vs Measurement System

Nur Afny C. Andryani, Kadek Dwi Pradnyana, Dadang Gunawan
2019 Journal of Physics, Conference Series  
As long as the signal can be guaranteed sparse, the CS based method is able to provide high reconstruction accuracy.  ...  The lack of required sampling is no longer constraint for having good reconstruction performance. The load is shifted to the reconstruction procedure instead of the sampling acquisition process.  ...  The correlation of the mutual coherence as the independent variable and the R as the dependent variable is evaluated using Pearson Correlation test, which is presented on Table 4 .  ... 
doi:10.1088/1742-6596/1196/1/012074 fatcat:gsdysbt6onbpbp7md4udtrv4fu

Modular Encoding and Decoding Models Derived from Bayesian Canonical Correlation Analysis

Yusuke Fujiwara, Yoichi Miyawaki, Yukiyasu Kamitani
2013 Neural Computation  
We develop a model based on Bayesian canonical correlation analysis, in which each module is modeled by a latent variable that relates a set of pixels in a visual image to a set of voxels in an fMRI activity  ...  The estimated mapping from a latent variable to pixels can be regarded as an image basis. We show that the model estimates a modular representation with spatially localized multiscale image bases.  ...  Next, we derive our Bayesian CCA model, which allows sparse selection of visual image pixels and fMRI voxels for each link. Canonical Correlation Analysis.  ... 
doi:10.1162/neco_a_00423 pmid:23339608 fatcat:nnfqgax4azhfvoq77qucnsuwya

Quantifying errors in observationally‐based estimates of ocean carbon sink variability

Lucas Gloege, Galen A. McKinley, Peter Landschützer, Amanda R. Fay, Thomas L. Frölicher, John C. Fyfe, Tatiana Ilyina, Steve Jones, Nicole S. Lovenduski, Christian Rödenbeck, Keith Rodgers, Sarah Schlunegger (+1 others)
2021 Global Biogeochemical Cycles  
The power of a testbed is that the perfect reconstruction is known for each of the original model fields; thus, reconstruction skill can be comprehensively assessed.  ...  For Southern Ocean decadal variability, insufficient sampling leads to a 31% (15%:58%, interquartile range) overestimation of amplitude, and phasing is only moderately correlated with known truth (r =  ...  Conflict of Interests The authors declare no conflicts of interest relevant to this study.  ... 
doi:10.1029/2020gb006788 fatcat:7qi2qtqiurfazjroxvoc7cjw4u

Data-driven sparse reconstruction of flow over a stalled aerofoil using experimental data

Douglas W. Carter, Francis De Voogt, Renan Soares, Bharathram Ganapathisubramani
2021 Data-Centric Engineering  
Recent work has demonstrated the use of sparse sensors in combination with the proper orthogonal decomposition (POD) to produce data-driven reconstructions of the full velocity fields in a variety of flows  ...  It is found that the linear reconstructions inspired by the extended POD are inferior to the compressed sensing approach provided that the sparse sensors avoid regions of the flow with small variance across  ...  John Lawson for his technical assistance with the PIV code. Funding Statement.  ... 
doi:10.1017/dce.2021.5 fatcat:7lsqhd7scrf6dlqntp7adtlw6e

Efficient coding correlates with spatial frequency tuning in a model of V1 receptive field organization

JAN WILTSCHUT, FRED H. HAMKER
2009 Visual Neuroscience  
Our simulation results indicate that most measures of efficient coding correlate with the similarity of model receptive field data to V1 data, that is, optimizing the estimate of efficient coding increases  ...  how different estimates of efficient coding in a model with nonlinear dynamics and Hebbian learning determine the similarity of model receptive fields to V1 data with respect to spatial tuning.  ...  Acknowledgments This work has been supported by the German Research Foundation (Deutsche Forschungsgemeinschaft) grant ''A neurocomputational systems approach to modeling the cognitive guidance of attention  ... 
doi:10.1017/s0952523809090051 fatcat:wkuslee5dnfr5exbltbkbmpzry

Efficient coding correlates with spatial frequency tuning in a model of V1 receptive field organization

Jan Wiltschut, Fred H Hamker
2009 BMC Neuroscience  
Our simulation results indicate that most measures of efficient coding correlate with the similarity of model receptive field data to V1 data, that is, optimizing the estimate of efficient coding increases  ...  how different estimates of efficient coding in a model with nonlinear dynamics and Hebbian learning determine the similarity of model receptive fields to V1 data with respect to spatial tuning.  ...  Acknowledgments This work has been supported by the German Research Foundation (Deutsche Forschungsgemeinschaft) grant ''A neurocomputational systems approach to modeling the cognitive guidance of attention  ... 
doi:10.1186/1471-2202-10-s1-p134 fatcat:rqusv5zjzvezrjdmenuchengfe

Efficient coding correlates with spatial frequency tuning in a model of V1 receptive field organization

JAN WILTSCHUT, FRED H. HAMKER
2009 Visual Neuroscience  
Our simulation results indicate that most measures of efficient coding correlate with the similarity of model receptive field data to V1 data, that is, optimizing the estimate of efficient coding increases  ...  how different estimates of efficient coding in a model with nonlinear dynamics and Hebbian learning determine the similarity of model receptive fields to V1 data with respect to spatial tuning.  ...  Acknowledgments This work has been supported by the German Research Foundation (Deutsche Forschungsgemeinschaft) grant ''A neurocomputational systems approach to modeling the cognitive guidance of attention  ... 
doi:10.1017/s0952523808080966 pmid:19203427 fatcat:yiyto3jjv5cd3ef5gnjxn6t2xa

Sparse ordinal logistic regression and its application to brain decoding [article]

Emi Satake, Kei Majima, Shuntaro Aoki, Yukiyasu Kamitani
2017 bioRxiv   pre-print
SOLR also outperformed classification and linear regression models with the same type of sparseness, indicating the advantage of the modeling tailored to ordinal outputs.  ...  To date, there is no established method of predicting ordinal variables in brain decoding.  ...  with the sparse estimation ( Figure 1C) samples and input dimensions in the simulation analysis.  ... 
doi:10.1101/238758 fatcat:grqflkixrvew5e4ndlim4ecpfm

Accelerated phase contrast flow imaging with direct complex difference reconstruction

Aiqi Sun, Bo Zhao, Ke Ma, Zechen Zhou, Le He, Rui Li, Chun Yuan
2016 Magnetic Resonance in Medicine  
Purpose-To propose and evaluate a new model-based reconstruction method for highly accelerated phase-contrast magnetic resonance imaging (PC-MRI) with sparse sampling.  ...  Conclusion- The proposed method achieves improved accuracy over several state-of-the-art methods for velocity reconstruction with highly accelerated (k, t)-space data  ...  Liang for hosting her visit to the University of Illinois at Urbana-Champaign, during which the initial concept of this work was developed.  ... 
doi:10.1002/mrm.26184 pmid:27016025 pmcid:PMC5734924 fatcat:yiq7eo4pvbg77pufvgmiwwscee

Sparse Ordinal Logistic Regression and Its Application to Brain Decoding

Emi Satake, Kei Majima, Shuntaro C. Aoki, Yukiyasu Kamitani
2018 Frontiers in Neuroinformatics  
with a mean of 1.0.  ...  Ordinal regression task with visual image reconstruction data. (A)Reconstruction procedure of Miyawaki et al. (2008).  ... 
doi:10.3389/fninf.2018.00051 pmid:30158864 fatcat:uvyoax6wzvcljb42y4tgnktopi

Message passing algorithms for the Hopfield network reconstruction: Threshold behavior and limitation

Haiping Huang
2010 Physical Review E  
The applied susceptibility propagation algorithm is shown to improve significantly on other mean-field-type methods and extends well into the low temperature region.  ...  The Hopfield network is reconstructed as an inverse Ising problem by passing messages.  ...  Acknowledgments Helpful discussions with Erik Aurell, Haijun Zhou and Pan Zhang are acknowledged.  ... 
doi:10.1103/physreve.82.056111 pmid:21230549 fatcat:3gtrfma3yncffohcsapkgvh3au

Sparse Hopfield network reconstruction with ℓ 1 regularization

Haiping Huang
2013 European Physical Journal B : Condensed Matter Physics  
The efficiency of this strategy is demonstrated for the sparse Hopfield model, but the method is generally applicable to other diluted mean field models.  ...  We propose an efficient strategy to infer sparse Hopfield network based on magnetizations and pairwise correlations measured through Glauber samplings.  ...  Acknowledgments Helpful discussions with Yoshiyuki Kabashima are gratefully acknowledged. This work was supported by the JSPS Fellowship for Foreign Researchers (Grant No. 24 · 02049).  ... 
doi:10.1140/epjb/e2013-40502-8 fatcat:pykb3fcmwfdm7d5msjf3kg4kce

Alternative methods of proxy-based climate field reconstruction: application to summer drought over the conterminous United States back to AD 1700 from tree-ring data

Zhihua Zhang, Michael E. Mann, Edward R. Cook
2004 The Holocene  
to calibration, with serial correlation added back into the reconstruction at the end of the procedure.  ...  We describe an alternative method of climate field reconstruction and test it against an existing set of dendroclimatic reconstructions of summer drought patterns over the conterminous US back to AD 1700  ...  fields, RE(m) is the RE value for multi-gridpoints (multivariate value), r(a) 2 is the squared correlation coefficient between actual PDSI and reconstructed PDSI for mean fields, r(m) 2 is the squared  ... 
doi:10.1191/0959683604hl727rp fatcat:fl3fhqoc7jfxbkqo3rvkb4wwha
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