Publikationen der AG Technomathematik

Zeitschriftenartikel (11)

1. C. Bockelmann, H. Schepker, A. Dekorsy, A. Bartels, D. Trede, K. Kazimierski.
   C-Curve: A Finite Alphabet based Parameter Choice Rule for Elastic-Net in Sporadic Communication.
   IEEE Communication Letters, 18(8):1443 -- 1446, 2014.

   DOI: 10.1109/LCOMM.2014.2329487

2. H. Thiele, S. Heldmann, D. Trede, J. Strehlow, S. Wirtz, W. Dreher, J. Berger, J. Oetjen, J. H. Kobarg, B. Fischer, P. Maaß.
   2D and 3D MALDI-Imaging: Conceptual Strategies for Visualization and Data Mining.
   BBA - Proteins and Proteomics, 1844(1):117-137, 2014.

   DOI: 10.1016/j.bbapap.2013.01.040

3. G. Ernst, O. Guntinas-Lichius, L. Hauberg-Lotte, D. Trede, M. Becker, F. Alexandrov, F. von Eggeling.
   Histomolecular interpretation of pleomorphic adenomas of the salivary gland by matrix-assisted laser desorption ionization imaging and spatial segmentation.
   Head & Neck, 37(7), 2014.

   DOI: 10.1002/hed.23713

4. B. Denkena, J. Vehmeyer, D. Niederwestberg, P. Maaß.
   Identification of the specific cutting force for geometrically defined cutting edges and varying cutting conditions.
   International Journal of Machine Tools and Manufacture, 82:42-49, 2014.

   DOI: 10.1016/j.ijmachtools.2014.03.009

5. O. Klein, K. Strohschein, G. Nebrich, J. Oetjen, D. Trede, H. Thiele, F. Alexandrov, P. Giavalisco, G. N. Duda, P. Roth von, S. Geissler, J. Klose, T. Winkler.
   MALDI imaging mass spectrometry: Discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures.
   Proteomics, 14(20):2249-2260, 2014.

   DOI: 10.1002/pmic.201400088

6. J. H. Kobarg, P. Maaß, J. Oetjen, O. Tropp, E. Hirsch, C. Sagiv, M. Goldabaee, P. Vandergheynst.
   Numerical experiments with MALDI Imaging data.
   Advances in Computational Mathematics, 40(3):667-682, 2014.

   DOI: 10.1007/s10444-013-9325-0

7. R. M. M. Abed, L. Polerecky, A. Al-Habsi, J. Oetjen, M. Strous, D. de Beer.
   Rapid Recovery of Cyanobacterial Pigments in Desiccated Biological Soil Crusts following Addition of Water.
   PLoS ONE, , 2014.

   DOI: 10.1371/journal.pone.0112372

8. M. Jiang, P. Maaß, T. Page.
   Regularizing properties of the Mumford-Shah functional for imaging applications.
   Inverse Problems, 30(3), 035007 , 2014.

   Ausgezeichnet als Highlight Paper

   DOI: 10.1088/0266-5611/30/3/035007

9. P. Maaß, C. Sagiv, H. Stark, B. Torresani.
   Signal representation, uncertainty principles and localization measures.
   Advances in Computational Mathematics, 40(3):597-607, Springer Verlag, 2014.

   DOI: 10.1007/s10444-014-9341-8

10. M. Gehre, T. Kluth, C. Sebu, P. Maaß.
    Sparse 3D reconstructions in electrical impedance tomography using real data.
    Inverse Problems in Science and Engineering, 22(1):31-44, Taylor & Francis, 2014.

    DOI: 10.1080/17415977.2013.827183

11. E. Herrholz, D. Lorenz, G. Teschke, D. Trede.
    Sparsity and Compressed Sensing in Inverse Problems.
    Lecture Notes in Computational Science and Engineering, 102:365-379, Springer Verlag, 2014.

    DOI: 10.1007/978-3-319-08159-5_18

Tagungsbeiträge (1)

1. P. Li, T. Page, G. Luo, W. Zhang, P. Zhang, P. Wang, P. Maaß, M. Jiang, J. Cong.
   FPGA Acceleration for Simultaneous Medical Image Reconstruction and Segmentation .
   2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines , 11.05.-13.05.2014, Boston, MA, USA.
   

   DOI: 10.1109/FCCM.2014.54

Qualifikationsarbeiten (3)

1. A. Bartels.
   Data Compression and Compressed Sensing in Imaging Mass Spectrometry and Sporadic Communication.
   Dissertationsschrift, Universität Bremen, Logos Verlag, 2014.

   online unter: http://www.logos-verlag.de/cgi-bin/buch/isbn/3850

2. R. Strehlow.
   Regularization of the inverse medium problem : on nonstandard methods for sparse reconstruction.
   Dissertationsschrift, Universität Bremen, 2014.

   online unter: http://elib.suub.uni-bremen.de/edocs/00104187-1.pdf

3. J. H. Kobarg.
   Signal and image processing methods for imaging mass spectrometry data.
   Dissertationsschrift, Universität Bremen, 2014.

   online unter: http://nbn-resolving.de/urn:nbn:de:gbv:46-00104098-10

Sonstiges (1)

1. P. Gralla.
   Inverse Problems Using Reduced Basis Method.
   All Theses, 2014.

   Master Thesis

   online unter: http://tigerprints.clemson.edu/all_theses/2007