Spike detection from inaccurate samplings

[1]  Gabriel Peyré,et al.  Exact Support Recovery for Sparse Spikes Deconvolution , 2013, Foundations of Computational Mathematics.

[2]  松井 秀俊.  Statistics for High-Dimensional Data: Methods, Theory and Applications, Peter Buhlman and Sara van de Geer著, Springer, 2011年6月, 558pp., 価格 114,99〓, ISBN 978-3642201912 , 2014 .

[3]  Gongguo Tang,et al.  Near minimax line spectral estimation , 2013, 2013 47th Annual Conference on Information Sciences and Systems (CISS).

[4]  Carlos Fernandez-Granda.  Support detection in super-resolution , 2013, ArXiv.

[5]  K. Bredies,et al.  Inverse problems in spaces of measures , 2013 .

[6]  Emmanuel J. Candès,et al.  Super-Resolution from Noisy Data , 2012, Journal of Fourier Analysis and Applications.

[7]  Jari Lindberg,et al.  Mathematical concepts of optical superresolution , 2012 .

[8]  Emmanuel J. Candès,et al.  Towards a Mathematical Theory of Super‐resolution , 2012, ArXiv.

[9]  E. Candès,et al.  Compressive fluorescence microscopy for biological and hyperspectral imaging , 2012, Proceedings of the National Academy of Sciences.

[10]  Sara van de Geer,et al.  Statistics for High-Dimensional Data: Methods, Theory and Applications , 2011 .

[11]  Yohann de Castro,et al.  Exact Reconstruction using Beurling Minimal Extrapolation , 2011, 1103.4951.

[12]  Otmar Scherzer,et al.  Sparsity Regularization for Radon Measures , 2009, SSVM.

[13]  Otmar Scherzer,et al.  Variational Methods in Imaging , 2008, Applied mathematical sciences.

[14]  O. Scherzer,et al.  A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators , 2007 .

[15]  B. Dumitrescu.  Positive Trigonometric Polynomials and Signal Processing Applications , 2007 .

[16]  Jean-Marc Azais Mario Wschebor.  A general expression for the distribution of the maximum of a Gaussian field and the approximation of the tail , 2006, math/0607041.

[17]  O. Scherzer,et al.  Error estimates for non-quadratic regularization and the relation to enhancement , 2006 .

[18]  S. Osher,et al.  Convergence rates of convex variational regularization , 2004 .

[19]  Moon Gi Kang,et al.  Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..

[20]  C. Zălinescu.  Convex analysis in general vector spaces , 2002 .

[21]  Fabrice Gamboa,et al.  Sets of Superresolution and the Maximum Entropy Method on the Mean , 1996 .

[22]  Fabrice Gamboa,et al.  Superresolution Rates in Prokhorov Metric , 1996, Canadian Journal of Mathematics.

[23]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[24]  P. Borwein,et al.  Polynomials and Polynomial Inequalities , 1995 .

[25]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[26]  D. Donoho.  Superresolution via sparsity constraints , 1992 .

[27]  M. Kreĭn,et al.  The Markov Moment Problem and Extremal Problems , 1977 .

[28]  W. Rudin.  Real and complex analysis , 1968 .