Publications

T. Hrycak, S. Schmutzhard: “Error bounds for the numerical evaluation of Legendre polynomials by a three-term recurrence”, Electronic Transactions on Numerical Analysis (2021), DOI: 10.1553/etna vol54s323

T. Hrycak, S. Schmutzhard: “Evaluation of Legendre polynomials by a three-term recurrence in floating-point arithmetic”, IMA Journal of Numerical Analysis (2020), DOI: 10.1093/imanum/dry079

V. Chatziioannou, S. Schmuthard, M. Pàmies-Vilà, A. Hofmann: “Investigating Clarinet Articulation Using a Physical Model and an Artificial Blowing Machine”, Acta Acustica united with Acustica (2019), DOI: 10.3813/aaa.919348

T. Hrycak, S. Schmutzhard: “Accurate evaluation of Chebyshev polynomials in floating-point arithmetic”, BIT Numerical Mathematics (2019), DOI: 10.1007/s10543-018-0738-5

T. Hrycak, S. Schmutzhard: “Inequalities involving Gegenbauer polynomials and their tangent lines”, Mathematical Inequalities & Applications (2019), DOI: 10.7153/mia-2019-22-26.

T. Hrycak, S. Schmutzhard: “Evaluation of Chebyshev polynomials by a three-term recurrence in floating-point arithmetic”, BIT Numerical Mathematics (2017), doi.org/10.1007/s10543-017-0683-8.

B. Wang, S. Mosbach, S. Schmutzhard, S. Shuai, Y. Huang, M. Kraft: “Modelling soot formation from wall films in a gasoline direct injection engine using a detailed population balance model ”, Applied Energy, Volume 163, Pages 154–166, 2016.

T. Hrycak, S. Schmutzhard: “A Nicholson-type integral for the crossproduct of the Bessel functions”, J. Math. Anal. Appl., Volume 436(1), Pages 168–178, 2016.

S. Schmutzhard, T. Hrycak, H. G. Feichtinger: “A numerical study of the Legendre-Galerkin method for the evaluation of the prolate spheroidal wave functions”, Numerical Algorithms, Volume 68(4), Pages 691–710, 2015.

A. Jung, S. Schmutzhard, F. Hlawatsch: “The RKHS Approach to Minimum Variance Estimation Revisited: Exponential Families, Sufficient Statistics and Variance Bounds”, IEEE Transactions on Information Theory, 60(7), pages 4050–4065, 2014.

A. Jung, S. Schmutzhard, F. Hlawatsch, Z. Ben-Haim, Y. C. Eldar: “Minimum Variance Estimation of Sparse Vectors within the Linear Gaussian Model: An RKHS Approach”, IEEE Transactions on Information Theory, 60(10), pages 6555–6575, 2014.

V. Nestoridis, S. Schmutzhard, V. Stefanopoulos: “Universal series induced by approximate identities and some relevant applications”, Journal of Approximation Theory, 2011, doi: 10.1016/j.jat.2011.06.001.