Institut für Mathematik > Mitarbeiter > Maryam Pazouki
Dr. Maryam Pazouki
TU Clausthal
Institut für Mathematik
Arbeitsgruppe Stochastische Modelle in den Ingenieurwissenschaften
Raum 102 / Erzstraße 1
38678 Clausthal
Telefon: +49 5323 72-2407
Fax: +49 5323 72-2304 (Sekretariat)
E-Mail: maryam.pazouki@tu-clausthal.de
Publications
- Maryam Pazouki, S. Seyedallaei, D. P. F. Möller, ”Adaptive Learning Algorithm for RBF Neural Networks in Kernel Spaces”, Appear in IEEE World Congress on Computational Intelligence (IEEE WCCI) 2016.
- M. Pazouki, S. S. Allaei, and D. P. F. Möller, "Artificial Neural Networks for Solving Integral Equations", ongoing project.
- Maryam Pazouki, Z. Wu, Z. Yang, D. P. F. Möller, ”An efficient learning method for RBF Neural Networks”, IEEE Neural Networks, International Joint Conference on Neural Networks(IJCNN), pp. 1-6, (2015) DOI 10.1109/IJCNN.2015.7280758
- Siamak Azodolmolky, Reza Nejabati, Maryam Pazouki, Philipp Wieder, Ramin Yahyapour and Dimitra Simeonidou, ”An Analytical Model for Software Defined Networking: A Network Calculus–based Approach”, IEEE GlobeCom, pp 1397 - 1402 (2013), DOI 10.1109/GLOCOM.2013.6831269.
- Maryam Pazouki, Robert Schaback, ”Bases for Conditionally Positive Definite Kernels”, Computational and Applied Mathematics 243(2013), pp. 152-163.
- Maryam Pazouki, "Stable Bases for Kernel Based Methods", Dissertation, Göttingen(2012). https://ediss.uni-goettingen.de/handle/11858/00-1735-0000-0010-D298-8?show=full.
- Maryam Pazouki, Robert Schaback,”Bases for Kernel-Bases Spaces”, Computational and Applied Mathematics 236(2011), pp. 575-588.