Publications about 'Algebra'

Books and proceedings

1. Zhi-Hua Zhou. Machine Learning. Springer Singapore, 2021. Keyword(s): Machine Learning, Book on Machine Learning, Computer Science, Learning Algorithms, Neural Networks, Support Vector Machines, Decision Trees, Classification, Clustering, Supervised Learning, Semi-Supervised Learning, Unsupervised Learning, Metric Learning, Feature Selection, Rule Learning, Mathematical Models, Reinforcement Learning, Bayesian Networks, ML, AI, Artificial Intelligence. [Abstract] [bibtex-entry]



2. Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Mathematics for Machine Learning. Campbridge University Press, 2020. Keyword(s): Machine Learning, Textbook, Introduction to Machine Learning, Mathematical Foundations, Linear Algebra, Analytic Geometry, Matrix Decompositions, Vector Calculus, Probability, Distributions, Optimization, Central Machine Learning Problems, Models and Data, Linear Regression, Dimensionality Reduction, Principle Components Analysis, Density Estimation, Gaussian Mixture, Support Vector Machines. [bibtex-entry]

Articles in journal or book chapters

1. B. Minchew, C.E. Jones, and B. Holt. Polarimetric Analysis of Backscatter From the Deepwater Horizon Oil Spill Using L-Band Synthetic Aperture Radar. Geoscience and Remote Sensing, IEEE Transactions on, 50(10):3812-3830, October 2012. Keyword(s): AD 2010 06 23, Bragg scattering mechanism, DWH slick, Gulf of Mexico, L-band synthetic aperture radar, backscatter polarimetric analysis, coherency matrix eigenvalue, deepwater horizon, deepwater horizon oil spill, dielectric constant, entropy parameters, fully-polarimetric uninhabited aerial vehicle, ocean wave spectral components, oil slick, oil volumetric concentration, radar backscatter, sea water, slick detection method, substantial variation parameter, surface scattering analysis, synthetic aperture radar data, backscatter, eigenvalues and eigenfunctions, entropy, marine pollution, matrix algebra, ocean chemistry, ocean waves, oceanographic regions, oceanographic techniques, permittivity, radar interferometry, remote sensing by radar, seawater, synthetic aperture radar;. [Abstract] [bibtex-entry]



2. Stefano Tebaldini and Fabio Rocca. Multibaseline Polarimetric SAR Tomography of a Boreal Forest at P- and L-Bands. IEEE Trans. Geosci. Remote Sens., 50(1):232-246, January 2012. Keyword(s): SAR Processing, SAR Tomography, Tomography, ESA campaign BioSAR, Krycklan River catchment, L-band analysis, Northern Sweden, P-band analysis, PolInSAR approach, algebraic synthesis technique, boreal forest, direct volume backscattering process, ground-volume interaction process, multibaseline polarimetric SAR tomography, multipolarimetric data acquisition, polarimetric analysis, remote sensing, single-baseline data analysis, tomographic analysis, tomographic imaging method, vegetation layer analysis, backscatter, data acquisition, forestry, radar interferometry, radar polarimetry, remote sensing by radar, rivers, synthetic aperture radar, tomography, vegetation mapping;. [Abstract] [bibtex-entry]



3. Guido Gatti, Stefano Tebaldini, Mauro Mariotti d'Alessandro, and Fabio Rocca. ALGAE: A Fast Algebraic Estimation of Interferogram Phase Offsets in Space-Varying Geometries. IEEE Trans. Geosci. Remote Sens., 49(6):2343-2353, June 2011. Keyword(s): SAR Processing, SAR Tomography, Tomography, ALGAE, DLR, E-SAR airborne system, ESA BIOSAR 2008 campaign, European Space Agency, Experimental SAR airborne system, German Aerospace Center, P-band data set, airborne multipass interferometric campaigns, data stack phase locking, incidence angle sensitivity, interferogram phase offset algebraic estimation, interferogram phase offset compensation, multipass InSAR analysis, null space component identification, space varying geometries, synthetic aperture radar interferometry, system geometry space varying nature, system geometry variation, terrain topography estimation, terrain topography retrieval, geophysical signal processing, linear algebra, radar interferometry, radar signal processing, remote sensing by radar, synthetic aperture radar, terrain mapping, topography (Earth);. [Abstract] [bibtex-entry]



4. E.J. Candes and Y. Plan. Matrix Completion With Noise. Proceedings of the IEEE, 98(6):925-936, june 2010. Keyword(s): compressed sensing, convex optimization problem, data constraints, low rank matrices, matrix completion, nuclear norm minimization, data integrity, matrix algebra, minimisation, noise, signal sampling;. [Abstract] [bibtex-entry]



5. R. L. Morrison, M. N. Do, and D. C. Munson. MCA: A Multichannel Approach to SAR Autofocus. IEEE Transactions on Image Processing, 18(4):840-853, April 2009. Keyword(s): SAR Processing, Autofocus, SAR autofocus, defocusing operation, focused image, image restoration, linear algebraic formulation, multichannel autofocus, multichannel redundancy, sharpness metric optimization, synthetic aperture radar, vector-space formulation, image restoration, linear algebra, synthetic aperture radar;. [Abstract] [bibtex-entry]



6. S. Ozsoy and A.A. Ergin. Pencil Back-Projection Method for SAR Imaging. IEEE Transactions on Image Processing, 18(3):573-581, March 2009. Keyword(s): SAR Processing, SAR Tomography, Tomography, SAR imaging, forward-backward total least squares bandpass matrix pencil method, pencil back-projection method, projected target reflectivity density function, synthetic aperture radar, tomographic image reconstruction, image reconstruction, least squares approximations, matrix algebra, radar imaging, synthetic aperture radar, Algorithms, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Radar, Reproducibility of Results, Sensitivity and Specificity, Tomography;. [Abstract] [bibtex-entry]



7. Stefano Tebaldini. Algebraic Synthesis of Forest Scenarios From Multibaseline PolInSAR Data. IEEE Trans. Geosci. Remote Sens., 47(12):4132-4142, December 2009. Keyword(s): SAR Processing, SAR Tomography, Tomography, E-SAR, P-Band, algebra, geophysical techniques, radar polarimetry, remote sensing by radar, synthetic aperture radar, vegetationBioSAR, E-SAR airborne system, Kronecker products sum, P-band data set, Remningstorp, SAR surveys, Sweden, algebraic synthesis, forest scenarios, forested areas, least square solution, multibaseline PolInSAR data, multipolarimetric multibaseline synthetic aperture radar, single-baseline polarimetric SAR interferometry, statistical uncorrelation, temporal coherence losses, volumetric coherence losses. [Abstract] [bibtex-entry]



8. B.D. Carlson. Covariance matrix estimation errors and diagonal loading in adaptive arrays. IEEE Transactions on Aerospace and Electronic Systems, 24(4):397-401, July 1988. Keyword(s): SAR Processing, Beamforming, array processing, antenna phased arrays, antenna theory, digital simulation, eigenvalues and eigenfunctions, estimation theory, matrix algebraadapted antenna patterns, adaptive arrays, covariance matrix sample size, diagonal loading, distorted mainbeams, eigenvector decomposition, estimation errors, low-level interference, nulling, sample matrix inversion, sidelobes. [Abstract] [bibtex-entry]



9. John W. Brewer. Kronecker products and matrix calculus in system theory. IEEE Transactions on Circuits and Systems, 25(9):772-781, September 1978. Keyword(s): Algebra, Algebraic and geometric techniques, Linear systems, time-invariant continuous-time, Matrix functions, Parameter identification, Algebra, Calculus, Feedback, Helium, Matrices, Sensitivity analysis, Steady-state, Stochastic systems, Subspace constraints, Sufficient conditions. [Abstract] [bibtex-entry]

Conference articles

1. E. Candes, Xiaodong Li, Yi Ma, and J. Wright. Robust principal component analysis?: Recovering low-rank matrices from sparse errors. In Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop, pages 201-204, October 2010. Keyword(s): bioinformatics, computer vision, low rank data matrix, nonvanishing fraction, nuclear norm, positive fraction, robust principal component analysis, simple convex program, weighted combination, matrix algebra, principal component analysis;. [Abstract] [bibtex-entry]



2. Andreas Reigber, Maxim Neumann, Stephane Guillaso, Stefan Sauer, and Laurent Ferro-Famil. Evaluating PolInSAR parameter estimation using tomographic imaging results. In Proc. European Radar Conf., pages 189-192, 2005. Keyword(s): SAR Processing, SAR Tomography, Tomography, forestry, matrix algebra, radar imaging, radar polarimetry, radiowave interferometry, remote sensing by radar, synthetic aperture radar, tomography, vegetation mapping, PolInSAR parameter estimation, canopy, forest height, ground topography estimation, polarimetric SAR interferometry, tomographic imaging results. [Abstract] [bibtex-entry]

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This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.

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