A fast and sensitive new satellite SO2retrieval algorithm based on principal component analysis: Application to the ozone monitoring instrument

Can Li; Joanna Joiner; Nickolay A. Krotkov; Pawan K. Bhartia

doi:10.1002/2013gl058134

A fast and sensitive new satellite SO2retrieval algorithm based on principal component analysis: Application to the ozone monitoring instrument

Geophysical Research Letters ◽

10.1002/2013gl058134 ◽

2013 ◽

Vol 40 (23) ◽

pp. 6314-6318 ◽

Cited By ~ 115

Author(s):

Can Li ◽

Joanna Joiner ◽

Nickolay A. Krotkov ◽

Pawan K. Bhartia

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Ozone Monitoring Instrument ◽

Monitoring Instrument ◽

Analysis Application ◽

Ozone Monitoring

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Intelligent diagnosis method using probability density distribution and principal component analysis — Application on gear rotating machinery

2016 International Symposium on Flexible Automation (ISFA) ◽

10.1109/isfa.2016.7790194 ◽

2016 ◽

Cited By ~ 1

Author(s):

Liuyang Song ◽

Peng Chen ◽

Huaqing Wang

Keyword(s):

Principal Component Analysis ◽

Density Distribution ◽

Probability Density ◽

Principal Component ◽

Component Analysis ◽

Rotating Machinery ◽

Probability Density Distribution ◽

Intelligent Diagnosis ◽

Diagnosis Method ◽

Analysis Application

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PV shading fault detection and classification based on I-V curve using principal component analysis: Application to isolated PV system

Solar Energy ◽

10.1016/j.solener.2018.12.048 ◽

2019 ◽

Vol 179 ◽

pp. 1-10 ◽

Cited By ~ 27

Author(s):

S. Fadhel ◽

C. Delpha ◽

D. Diallo ◽

I. Bahri ◽

A. Migan ◽

...

Keyword(s):

Principal Component Analysis ◽

Fault Detection ◽

Principal Component ◽

Component Analysis ◽

Pv System ◽

Fault Detection And Classification ◽

Analysis Application

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Improving Earthquake Prediction with Principal Component Analysis: Application to Chile

Lecture Notes in Computer Science - Hybrid Artificial Intelligent Systems ◽

10.1007/978-3-319-19644-2_33 ◽

2015 ◽

pp. 393-404 ◽

Cited By ~ 6

Author(s):

Gualberto Asencio-Cortés ◽

Francisco Martínez-Álvarez ◽

Antonio Morales-Esteban ◽

Jorge Reyes ◽

Alicia Troncoso

Keyword(s):

Principal Component Analysis ◽

Earthquake Prediction ◽

Principal Component ◽

Component Analysis ◽

Analysis Application

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Analysis Method Combining Monte Carlo Simulation and Principal Component Analysis –Application to Sourlas Code–

Journal of the Physical Society of Japan ◽

10.1143/jpsj.75.084003 ◽

2006 ◽

Vol 75 (8) ◽

pp. 084003 ◽

Cited By ~ 4

Author(s):

Masato Inoue ◽

Koji Hukushima ◽

Masato Okada

Keyword(s):

Principal Component Analysis ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Principal Component ◽

Component Analysis ◽

Analysis Method ◽

Analysis Application

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A nonlinear neural network model of mixture of local principal component analysis: application to handwritten digits recognition

Pattern Recognition ◽

10.1016/s0031-3203(00)00009-1 ◽

2001 ◽

Vol 34 (2) ◽

pp. 203-214 ◽

Cited By ~ 29

Author(s):

Bailing Zhang ◽

Minyue Fu ◽

Hong Yan

Keyword(s):

Neural Network ◽

Principal Component Analysis ◽

Network Model ◽

Neural Network Model ◽

Principal Component ◽

Component Analysis ◽

Analysis Application

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Modal Characterization using Principal Component Analysis: application to Bessel, higher-order Gaussian beams and their superposition

Scientific Reports ◽

10.1038/srep01422 ◽

2013 ◽

Vol 3 (1) ◽

Cited By ~ 17

Author(s):

A. Mourka ◽

M. Mazilu ◽

E. M. Wright ◽

K. Dholakia

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Higher Order ◽

Gaussian Beams ◽

Analysis Application

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Fault Detection and Isolation in Dynamic Systems Using Principal Component Analysis - Application to an Heating System Benchmark

IFAC Proceedings Volumes ◽

10.1016/s1474-6670(17)36543-6 ◽

2003 ◽

Vol 36 (5) ◽

pp. 513-518 ◽

Cited By ~ 1

Author(s):

Stéphane Léger ◽

Frédéric Hamelin ◽

Dominique Sauter

Keyword(s):

Principal Component Analysis ◽

Fault Detection ◽

Dynamic Systems ◽

Principal Component ◽

Heating System ◽

Component Analysis ◽

Fault Detection And Isolation ◽

Analysis Application

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Principal component analysis application in polycyclic aromatic hydrocarbons “mussel watch” analyses for source identification

Analytica Chimica Acta ◽

10.1016/s0003-2670(02)00274-x ◽

2002 ◽

Vol 461 (2) ◽

pp. 201-213 ◽

Cited By ~ 25

Author(s):

Anna Stella ◽

Maria Teresa Piccardo ◽

Rosella Coradeghini ◽

Anna Redaelli ◽

Silvia Lanteri ◽

...

Keyword(s):

Principal Component Analysis ◽

Polycyclic Aromatic Hydrocarbons ◽

Aromatic Hydrocarbons ◽

Source Identification ◽

Principal Component ◽

Component Analysis ◽

Mussel Watch ◽

Polycyclic Aromatic ◽

Analysis Application

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Automatic computation of regions of interest by robust principal component analysis. Application to automatic dementia diagnosis

Knowledge-Based Systems ◽

10.1016/j.knosys.2017.02.025 ◽

2017 ◽

Vol 123 ◽

pp. 229-237 ◽

Cited By ~ 4

Author(s):

Francisco Lozano ◽

Andrés Ortiz ◽

Jorge Munilla ◽

Alberto Peinado ◽

for the Alzheimer’s Disease Neuroimaging Initiative

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Regions Of Interest ◽

Dementia Diagnosis ◽

Robust Principal Component Analysis ◽

Automatic Computation ◽

Analysis Application

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Extraction of near infra-red spectral information by fast fourier transform and principal component analysis. Application to the discrimination of baking quality of wheat flours

Journal of Chemometrics ◽

10.1002/cem.1180010205 ◽

1987 ◽

Vol 1 (2) ◽

pp. 103-110 ◽

Cited By ~ 13

Author(s):

Marie-Françoise Devaux ◽

Dominique Bertrand ◽

Paul Robert ◽

Jean-Luc Morat

Keyword(s):

Principal Component Analysis ◽

Fourier Transform ◽

Fast Fourier Transform ◽

Principal Component ◽

Component Analysis ◽

Spectral Information ◽

Infra Red ◽

Analysis Application ◽

Wheat Flours

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