Current projects

RTG 2088: Discovering structure in complex data: Statistics meets Optimization and Inverse Problems (2015-2020)Speaker of the DFG Research Training Group | |

Fresnel wavelets for coherent diffractive imaging (2011-2019)DFG project (subproject C11) within the CRC 755 (Nanoscale Photonic Imaging, second and third funding period) | |

Efficient function reconstruction using eigenfunctions of linear operators (2014-2017)DFG project | |

Prony-like methods for noisy data (2015-2017)CSC grant |

Lecture: (WS 2017/2018)Approximation methods II (English)Tuesday and Friday 8.15 - 9.55, MN 55 (Lecture: 4 SWS + Exercises: 2 SWS / 9 ECTS) | |

Research seminar: Numerical Analysis (English) (WS 2017/2018)Thursday 12.30 - 14.00, Seminarraum NAM (2 SWS) |

Graph regularized seismic dictionary learningLina Liu, Jianwei Ma, Gerlind Plonka University of Göttingen, Institute for Numerical and Applied Mathematics, 2017 (preprint as download) | |

Application of the AAK theory for sparse approximation of exponential sumsGerlind Plonka, Vlada Pototskaia University of Göttingen, Institute for Numerical and Applied Mathematics, 2016 (preprint as download) | |

Deterministic sparse FFT for M-sparse vectorsGerlind Plonka, Katrin Wannenwetsch, Annie Cuyt, Wen-Shin Lee Numerical Algorithms, to appear, 2017 (revised preprint as download) | |

Enforcing uniqueness in one-dimensional phase retrieval by additional signal information in time domainRobert Beinert, Gerlind Plonka Applied and Computational Harmonic Analysis, to appear, 2017 (preprint as download (arXiv)) | |

Seismic data interpolation and denoising by learning a tensor tight frameLina Liu, Gerlind Plonka, Jianwei Ma Inverse Problems, to appear, 2017 (preprint as download) | |

A sparse Fast Fourier algorithm for real nonnegative vectorsGerlind Plonka, Katrin Wannenwetsch Journal of Computational and Applied Mathematics 321, 532-539, 2017 (preprint as download) | |

Sparse phase retrieval of one-dimensional signals by Prony's methodRobert Beinert, Gerlind Plonka Frontiers of Applied Mathematics and Statistics 3:5, 2017 (open access, preprint as download) | |

Iterative Phase Retrieval with Sparsity ConstraintsStefan Loock, Gerlind Plonka PAMM 16(1), 835-836, 2016 (DOI: 10.1002/pamm.201610406) | |

Sparse approximation by Prony's method and AAK theoryGerlind Plonka, Vlada Pototskaia Oberwolfach Reports, Volume 33, pp. 16-19, 2016 (preprint as download) | |

Using sparsity information for iterative phase retrieval in x-ray propagation imagingAnne Pein, Stefan Loock, Gerlind Plonka, Tim Salditt Opt. Express 24(8), 8332-8343., 2016 (open access) | |

Pseudo-inverses of difference matrices and their application to sparse signal approximationGerlind Plonka, Sebastian Hoffmann, Joachim Weickert Linear Algebra and its Applications 503, 26-47, 2016 (preprint as download) | |

Reconstruction of polygonal shapes from sparse Fourier samplesMarius Wischerhoff, Gerlind Plonka Journal of Computational and Applied Mathematics 297, 117-131, 2016 (preprint as download) | |

Relation between total variation and persistence distance and its application in signal processingGerlind Plonka, Yi Zheng Advances in Computational Mathematics 42(3), 651-674, 2016 (preprint (2014) as download) | |

A deterministic sparse FFT algorithm for vectors with small supportGerlind Plonka, Katrin Wannenwetsch Numerical Algorithms 71(4), 889-905, 2016 (preprint as download) | |

Deterministic sparse FFT algorithmsGerlind Plonka, Katrin Wannenwetsch Proc. Appl. Math. Mech. Volume 15, Issue 1, pp. 667-668, October 2015 (DOI: 10.1002/pamm.201510323, preprint as download) | |

Prony's Method for Multivariate SignalsThomas Peter, Gerlind Plonka, Robert Schaback Proc. Appl. Math. Mech. Volume 15, Issue 1, pp. 665-666, October 2015 (DOI: 10.1002/pamm.201510322, preprint as download) | |

Ambiguities in one-dimensional phase retrieval of structured functionsRobert Beinert, Gerlind Plonka Proc. Appl. Math. Mech. Volume 15, Issue 1, pp. 653-654, October 2015 (DOI: 10.1002/pamm.201510316, preprint as download) | |

A deterministic sparse FFT algorithm for vectors with short supportGerlind Plonka, Katrin Wannenwetsch Oberwolfach Reports, Volume 38, pp. 41-44, 2015 | |

CurveletsGerlind Plonka, Jianwei Ma Encyclopedia of Applied and Computational Mathematics, B. Engquist (eds.), 2015 (pp. 320-321, Springer Berlin, DOI 10.1007/978-3-540-70529-1) | |

Discrete Green's functions for harmonic and biharmonic inpainting with sparse atomsSebastian Hoffmann, Gerlind Plonka, Joachim Weickert X.-C. Tai et al. (Eds.): Energy Minimization Methods in Computer Vision and Pattern Recognition. LNCS 8932, Springer, Berlin, pp. 169-182, 2015 (preprint as download) | |

further publications... |

Easy Path Wavelet Transform (EPWT)Wavelet shrinkage on paths for denoising of scattered data including an adaptive deterministic and an adaptive random path construction. Dennis Heinen, Gerlind Plonka, Stefanie Tenorth | |

Sparse FFT (small support)A new deterministic sparse FFT algorithm for vectors with small support. Katrin Wannenwetsch, Gerlind Plonka | |

Sparse FFT (real non-negative)A new deterministic sparse FFT algorithm for real non-negative vectors. Katrin Wannenwetsch, Gerlind Plonka | |

Deterministic Sparse FFTDeterministic sparse FFT for M-sparse vectors, implemented in MATLAB. Gerlind Plonka, Katrin Wannenwetsch |

Prof. Dr. Gerlind Plonka-Hoch

University of Göttingen

Institute for Numerical and Applied Mathematics

Lotzestr. 16-18

37083 Göttingen

Raum 117

Tel.: 0551-39-22115

plonka AT math.uni-goettingen.de