Functions of Matrices: Theory and Computation

Orientations and matrix function-based centralities in multiplex network analysis of urban public transport

Bergermann, K., & Stoll, M. (2021) · Applied Network Science · doi:10.1007/s41109-021-00429-9 · Cited by 17

Perturbations of functions of diagonalizable matrices

Gil’, M. I. (2010) · Electronic Journal of Linear Algebra · doi:10.13001/1081-3810.1375 · Cited by 17

Componentwise accurate fluid queue computations using doubling algorithms

Nguyen, G. T., & Poloni, F. (2014) · Numerische Mathematik · doi:10.1007/s00211-014-0675-4 · Cited by 17

The matrix sign function for solving surface wave problems in homogeneous and laterally periodic elastic half-spaces

Norris, A. N., Shuvalov, A. L., & Kutsenko, A. A. (2013) · Wave Motion · doi:10.1016/j.wavemoti.2013.03.010 · Cited by 17

Several numerical methods for computing unitary polar factor of a matrix

Soleymani, F., Haghani, F. K., & Shateyi, S. (2016) · Advances in Difference Equations · doi:10.1186/s13662-015-0732-z · Cited by 17

Several properties of invariant pairs of nonlinear algebraic eigenvalue problems

Szyld, D. B., & Xue, F. (2013) · IMA Journal of Numerical Analysis · doi:10.1093/imanum/drt026 · Cited by 17

Analytical formula for two-dimensional ring artefact suppression

Titarenko, V. (2016) · Journal of Synchrotron Radiation · doi:10.1107/s160057751601479x · Cited by 17

Diffusion and consensus on weakly connected directed graphs

Veerman, J. J. P., & Kummel, E. (2019) · Linear Algebra and its Applications · doi:10.1016/j.laa.2019.05.014 · Cited by 17

A survey on the high convergence orders and computational convergence orders of sequences

Cătinaş, E. (2018) · Applied Mathematics and Computation · doi:10.1016/j.amc.2018.08.006 · Cited by 17

Minimal geodesics on GL(n) for left-invariant, right-O(n)-invariant Riemannian metrics

Martin, R. J., & Neff, P. (2016) · The Journal of Geometric Mechanics · doi:10.3934/jgm.2016010 · Cited by 17

Numerical Solution of Systems of Linear Algebraic Equations with Ill-Conditioned Matrices

Lebedeva, A. V., & Ryabov, V. M. (2019) · Vestnik St Petersburg University Mathematics · doi:10.1134/s1063454119040058 · Cited by 16

Efficient Compact Bilinear Pooling via Kronecker Product

Yu, T., Cai, Y., & Li, P. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i3.20225 · Cited by 16

Learning Partial Correlation based Deep Visual Representation for Image Classification

Rahman, S., Koniusz, P., Wang, L., Zhou, L., Moghadam, P., & Sun, C. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00603 · Cited by 16

Matrix-weighted Besov-type and Triebel–Lizorkin-type spaces I: $$A_p$$-dimensions of matrix weights and $$\varphi $$-transform characterizations

Bu, F., Hytönen, T., Yang, D., & Yuan, W. (2025) · Mathematische Annalen · doi:10.1007/s00208-024-03059-5 · Cited by 16

The Graph Fractional Fourier Transform in Hilbert Space

Zhang, Y., & Li, B. (2025) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2025.3540714 · Cited by 16

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)

Filippone, M., & Engler, R. (2015) · ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) · doi:10.48550/arxiv.1501.05427 · Cited by 16

The solution of two-dimensional advection–diffusion equations via operational matrices

de la Hoz, F., & Vadillo, F. (2013) · Applied Numerical Mathematics · doi:10.1016/j.apnum.2013.06.006 · Cited by 16

The structured distance to normality of banded Toeplitz matrices

Noschese, S., & Lothar Reichel, B. (2009) · BIT Numerical Mathematics · doi:10.1007/s10543-009-0231-2 · Cited by 16

A backward/forward recovery approach for the preconditioned conjugate gradient method

Fasi, M., Julien Langou, F., Robert, Y. L., & Uçar, B. (2016) · Journal of Computational Science · doi:10.1016/j.jocs.2016.04.008 · Cited by 16

Exponential integrator methods for systems of non-linear space-fractional models with super-diffusion processes in pattern formation

Iyiola, O. S., & Wade, B. A. (2018) · Computers & Mathematics with Applications · doi:10.1016/j.camwa.2018.02.027 · Cited by 16

A fourth-order method for computing the sign function of a matrix with application in the Yang–Baxter-like matrix equation

Soleymani, F., & Kumar, A. (2019) · Computational and Applied Mathematics · doi:10.1007/s40314-019-0816-6 · Cited by 16

Embeddability and rate identifiability of Kimura 2-parameter matrices

Casanellas, M., Fernández-Sánchez, J., & Roca-Lacostena, J. (2019) · Journal of Mathematical Biology · doi:10.1007/s00285-019-01446-0 · Cited by 16

Algorithms for the computation of the matrix logarithm based on the double exponential formula

Tatsuoka, F., Sogabe, T., Miyatake, Y., & Zhang, S. (2019) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2019.112396 · Cited by 16

Deep Global Generalized Gaussian Networks

Wang, Q., Li, P., Hu, Q., Zhu, P., & Zuo, W. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00522 · Cited by 16

Limited‐memory polynomial methods for large‐scale matrix functions

Güttel, S., Kreßner, D., & Lund, K. (2020) · GAMM-Mitteilungen · doi:10.1002/gamm.202000019 · Cited by 18

Computing low‐rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods

Kandolf, P., Koskela, A., Relton, S. D., & Schweitzer, M. (2021) · Numerical Linear Algebra with Applications · doi:10.1002/nla.2401 · Cited by 16

Rational Krylov methods for fractional diffusion problems on graphs

Michele Benzi, A., & Simunec, I. (2021) · BIT Numerical Mathematics · doi:10.1007/s10543-021-00881-0 · Cited by 16

Quantum Perturbation Theory Using Tensor Cores and a Deep Neural Network

Finkelstein, J., Rubensson, E. H., Mniszewski, S. M., Negre, C. F. A., & Niklasson, A. M. N. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00274 · Cited by 16

Solving Large‐Scale Linear Systems of Equations by a Quantum Hybrid Algorithm

Perelshtein, M. R., Pakhomchik, A. I., Мельников, А. А., Novikov, A. A., Glatz, A., Paraoanu, G. S., Vinokur, V. M., & Lesovik, G. B. (2022) · Annalen der Physik · doi:10.1002/andp.202200082 · Cited by 16

Two-Phase Image Segmentation by the Allen-Cahn Equation and a Nonlocal Edge Detection Operator

Qiao, Z., & Zhang, Q. (2022) · Numerical Mathematics Theory Methods and Applications · doi:10.4208/nmtma.oa-2022-0008s · Cited by 16

Randomized Sketching for Krylov Approximations of Large-Scale Matrix Functions

Güttel, S., & Schweitzer, M. (2023) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/22m1518062 · Cited by 16

Information mobility in complex networks

Estrada, E. (2009) · Physical Review E · doi:10.1103/physreve.80.026104 · Cited by 16

Numerical aspects of computing the Moore-Penrose inverse of full column rank matrices

Smoktunowicz, A., & Wróbel, I. (2011) · BIT Numerical Mathematics · doi:10.1007/s10543-011-0362-0 · Cited by 16

Stability for Fluid Queues: Characteristic Inequalities

Govorun, M., Latouche, G., & Remiche, M.-A. (2013) · Stochastic Models · doi:10.1080/15326349.2013.750533 · Cited by 16

Palindromic matrix polynomials, matrix functions and integral representations

Iannazzo, B., & Meini, B. (2010) · Linear Algebra and its Applications · doi:10.1016/j.laa.2010.09.013 · Cited by 16

Error bounds and estimates for Krylov subspace approximations of Stieltjes matrix functions

Frommer, A., & Schweitzer, M. (2015) · BIT Numerical Mathematics · doi:10.1007/s10543-015-0596-3 · Cited by 16

Two algorithms for computing the matrix cosine function

Sastre, J., Ibáñez, J., Alonso, P., Peinado, J., & Defez, E. (2017) · Applied Mathematics and Computation · doi:10.1016/j.amc.2017.05.019 · Cited by 16

Inexact Arnoldi residual estimates and decay properties for functions of non-Hermitian matrices

Pozza, S., & Simoncini, V. (2019) · BIT Numerical Mathematics · doi:10.1007/s10543-019-00763-6 · Cited by 16

Numerical computation and new output bounds for time-limited balanced truncation of discrete-time systems

Duff, I. P., & Kürschner, P. (2020) · Linear Algebra and its Applications · doi:10.1016/j.laa.2020.09.029 · Cited by 16

Manifold interpolation and model reductionPreprint

Zimmermann, R. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.06502 · Cited by 16

Artificial-Intelligence-Based Quantitative Fault Diagnosability Analysis of Spacecraft: An Information Geometry Perspective

Wang, D., Fu, F., Yu, H., Chu, W., Wu, Z., & Li, W. (2022) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2022.3162189 · Cited by 15

Topological invariants for interacting systems: From twisted boundary conditions to center-of-mass momentum

Lin, L., Ke, Y., & Lee, C. (2023) · Physical review. B./Physical review. B · doi:10.1103/physrevb.107.125161 · Cited by 16

A Lightweight Riemannian Covariance Matrix Convolutional Network for PolSAR Image Classification

Shi, J., Wang, W., Jin, H., Nie, M., & Ji, S. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3428835 · Cited by 15

Mathematical modeling of local balance in signed networks and its applications to global international analysis

Diaz-Diaz, F., Bartesaghi, P., & Estrada, E. (2024) · Journal of Applied Mathematics and Computing · doi:10.1007/s12190-024-02204-2 · Cited by 17

Low-rank Newton-ADI methods for large nonsymmetric algebraic Riccati equations

Benner, P., Kürschner, P., & Saak, J. (2015) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2015.04.016 · Cited by 15

A generalization of chang transformation for Linear Time-Varying systems

Yang, X., & Zhu, J. (2010) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2010.5717138 · Cited by 15

On the sign characteristics of Hermitian matrix polynomials

Mehrmann, V., Noferini, V., Françoise Tisseur, B., & Xu, H. (2016) · Linear Algebra and its Applications · doi:10.1016/j.laa.2016.09.002 · Cited by 15

Embedding-Based Interpolation on the Special Orthogonal Group

Gawlik, E. S., & Leok, M. B.-T. (2018) · SIAM Journal on Scientific Computing · doi:10.1137/17m1129416 · Cited by 15

Multichannel Sparse Blind Deconvolution on the Sphere

Li, Y., & Bresler, Y. (2019) · IEEE Transactions on Information Theory · doi:10.1109/tit.2019.2928576 · Cited by 15

Numerical solution for multi-dimensional Riesz fractional nonlinear reaction–diffusion equation by exponential Runge–Kutta method

Zhang, L., & Sun, H. (2019) · Journal of Applied Mathematics and Computing · doi:10.1007/s12190-019-01291-w · Cited by 15

Centrality measures for node-weighted networks via line graphs and the matrix exponential

Cabrera, O. D. L. C., Matar, M., & Lothar Reichel, B. (2021) · Numerical Algorithms · doi:10.1007/s11075-020-01050-0 · Cited by 15

Pseudospectral Shattering, the Sign Function, and Diagonalization in Nearly Matrix Multiplication Time

Banks, J., Garza-Vargas, J., Kulkarni, A., & Srivastava, N. (2020) · Annual Symposium on Foundations of Computer Science · doi:10.1109/focs46700.2020.00056 · Cited by 15

Fast and Compact Bilinear Pooling by Shifted Random Maclaurin

Yu, T., Li, X., & Li, P. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i4.16435 · Cited by 15

Krylov-Aware Stochastic Trace Estimation

Chen, T., & Hallman, E. (2023) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/22m1494257 · Cited by 15

Computing matrix functions arising in engineering models with orthogonal matrix polynomials

Defez, E., Sastre, J., Ibáñez, J., & Ruiz, P. A. (2011) · Mathematical and Computer Modelling · doi:10.1016/j.mcm.2011.11.022 · Cited by 15

Investigation on polynomial integrators for time-domain electromagnetics using a high-order discontinuous Galerkin method

Fahs, H. (2012) · Applied Mathematical Modelling · doi:10.1016/j.apm.2011.12.055 · Cited by 15

The Morphing of Fluid Queues into Markov-Modulated Brownian Motion

Latouche, G., & Nguyen, G. T. (2015) · Stochastic Systems · doi:10.1214/13-ssy133 · Cited by 15

Nonnegative square roots of matrices

Tam, B.-S., & Huang, P.-R. (2015) · Linear Algebra and its Applications · doi:10.1016/j.laa.2015.11.011 · Cited by 15

Simplified anti-Gauss quadrature rules with applications in linear algebra

Alqahtani, H., & Lothar Reichel, B. (2017) · Numerical Algorithms · doi:10.1007/s11075-017-0329-6 · Cited by 15

On the Stability of Network Indices Defined by Means of Matrix Functions

Pozza, S., & Tudisco, F. (2018) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/17m1133920 · Cited by 15

Averaging the population projection matrices: Heuristics against uncertainty and nonexistence

Logofet, D. O. (2017) · Ecological Complexity · doi:10.1016/j.ecocom.2017.12.003 · Cited by 15

Computing performability measures in Markov chains by means of matrix functions

Masetti, G., & Robol, L. (2019) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2019.112534 · Cited by 15

Covariance Matrices Encoding Based on the Log-Euclidean and Affine Invariant Riemannian Metrics

Ilea, I., Bombrun, L., Said, S., & Berthoumieu, Y. (2018) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2018.00080 · Cited by 15

Computable upper error bounds for Krylov approximations to matrix exponentials and associated $${\varvec{\varphi }}$$-functions

Jawecki, T., Auzinger, W., & Koch, O. (2019) · BIT Numerical Mathematics · doi:10.1007/s10543-019-00771-6 · Cited by 18

Predicting Triadic Closure in Networks Using Communicability Distance Functions

Estrada, E., & Arrigo, F. (2015) · SIAM Journal on Applied Mathematics · doi:10.1137/140996768 · Cited by 15

Accurate and efficient matrix exponential computation

Sastre, J., Ibáñez, J., Ruiz, P. A., & Defez, E. (2013) · International Journal of Computer Mathematics · doi:10.1080/00207160.2013.791392 · Cited by 15

Matrix exponentials and parallel prefix computation in a quantum control problem

Auckenthaler, T., Bader, M., Huckle, T., Spörl, A. K., & Waldherr, K. (2010) · Parallel Computing · doi:10.1016/j.parco.2010.01.006 · Cited by 15

Partial least squares for dependent data

Singer, M., Krivobokova, T., Munk, A., & de Groot, B. (2016) · Biometrika · doi:10.1093/biomet/asw010 · Cited by 15

Extremal Rational Functions on Symmetric Discrete Sets and Superlinear Convergence of the ADI Method

Beckermann, B., & Gryson, A. (2010) · Constructive Approximation · doi:10.1007/s00365-010-9087-6 · Cited by 15

Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian OptimizationPreprint

Pleiss, G., Jankowiak, M., Eriksson, D., Damle, A., & Gardner, J. R. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.11267 · Cited by 15

Output tracking for a 1-D heat equation with non-collocated configurations

Wu, X., & Feng, H. (2019) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2019.12.016 · Cited by 14

Adaptive optimal control of entangled qubits

Goodwin, D. L., Singh, P., & Foroozandeh, M. (2022) · Science Advances · doi:10.1126/sciadv.abq4244 · Cited by 14

Frequency domain Green’s function and boundary integral equations for multifield materials and quasicrystals

Pasternak, V., Sulym, H. Т., & Pasternak, I. M. (2023) · International Journal of Solids and Structures · doi:10.1016/j.ijsolstr.2023.112562 · Cited by 14

Efficient computation of enclosures for the exact solvents of a quadratic matrix equation

Hashemi, B., & Dehghan, M. (2010) · Electronic Journal of Linear Algebra · doi:10.13001/1081-3810.1391 · Cited by 14

The computation of the square roots of circulant matrices

Lu, C., & Gu, C. (2011) · Applied Mathematics and Computation · doi:10.1016/j.amc.2011.01.018 · Cited by 14

A Numerical Method for Computing the Principal Square Root of a Matrix

Soleymani, F., Shateyi, S., & Haghani, F. K. (2014) · Abstract and Applied Analysis · doi:10.1155/2014/525087 · Cited by 14

Classification and asymptotic structure of black holes in bimetric theory

Torsello, F., Kocic, M., & Mörtsell, E. (2017) · Physical review. D/Physical review. D. · doi:10.1103/physrevd.96.064003 · Cited by 17

A Rational Function Preconditioner For Indefinite Sparse Linear Systems

Xi, Y., & Saad, Y. (2017) · SIAM Journal on Scientific Computing · doi:10.1137/16m1078409 · Cited by 14

Efficient Implementation of Rational Approximations to Fractional Differential Operators

Aceto, L., & Novati, P. (2017) · Journal of Scientific Computing · doi:10.1007/s10915-017-0633-2 · Cited by 14

Computation of matrix gamma function

Cardoso, J. R., & Sadeghi, A. (2019) · BIT Numerical Mathematics · doi:10.1007/s10543-018-00744-1 · Cited by 14

Estimation of a multiplicative correlation structure in the large dimensional case

Hafner, C. M., Linton, O. B., & Tang, H. (2019) · Journal of Econometrics · doi:10.1016/j.jeconom.2019.12.012 · Cited by 14

Fast Converging Iterative Precoding for Massive MIMO Systems: An Accelerated Weighted Neumann Series-Steepest Descent Approach

Deng, Q., Liang, X., Wang, X., Huang, M., Dong, C., & Zhang, Y. (2020) · IEEE Access · doi:10.1109/access.2020.2979371 · Cited by 14

Frequency-Limited Reduction of Regular and Singular Circuit Models Via Extended Krylov Subspace Method

Floros, G., Evmorfopoulos, N., & Stamoulis, G. I. (2020) · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · doi:10.1109/tvlsi.2020.2994534 · Cited by 14

Analysis of Probing Techniques for Sparse Approximation and Trace Estimation of Decaying Matrix Functions

Frommer, A., Schimmel, C., & Schweitzer, M. (2021) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/20m1364461 · Cited by 14

A Multiprecision Derivative-Free Schur--Parlett Algorithm for Computing Matrix Functions

Higham, N. J., & Liu, X. (2021) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/20m1365326 · Cited by 14

Computing Eigenvalues of Diagonalizable Matrices on a Quantum Computer

Shao, C. (2022) · ACM Transactions on Quantum Computing · doi:10.1145/3527845 · Cited by 16

Contour Integral Methods for Nonlinear Eigenvalue Problems: A Systems Theoretic Approach

Brennan, M., Embree, M., & Serkan Gugercin, A. (2023) · SIAM Review · doi:10.1137/20m1389303 · Cited by 14

Second-order maximum principle preserving Strang’s splitting schemes for anisotropic fractional Allen-Cahn equations

Chen, H., & Sun, H. (2021) · Numerical Algorithms · doi:10.1007/s11075-021-01207-5 · Cited by 14

SPD-DDPM: Denoising Diffusion Probabilistic Models in the Symmetric Positive Definite Space

Li, Y., Yu, Z., He, G., Shen, Y., Li, K., Sun, X., & Lin, S. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i12.29276 · Cited by 16

On the Matrix Square Root via Geometric Optimization

Sra, S. (2016) · Electronic Journal of Linear Algebra · doi:10.13001/1081-3810.3196 · Cited by 14

Numerical investigation of a space-fractional model of turbulent fluid flow in rectangular ducts

Churbanov, A. G., & Vabishchevich, P. N. (2016) · Journal of Computational Physics · doi:10.1016/j.jcp.2016.06.009 · Cited by 14

On Best Approximations of Polynomials in Matrices in the Matrix 2-Norm

Liesen, J., & Tichý, P. (2009) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/080728299 · Cited by 14

Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons

Sadeh, S., Cardanobile, S., & Rotter, S. (2014) · SpringerPlus · doi:10.1186/2193-1801-3-148 · Cited by 14

Short-recurrence Krylov subspace methods for the overlap Dirac operator at nonzero chemical potential

Bloch, J., Breu, T., Frommer, A., Heybrock, S., Schäfer, K., & Tilo Wettig, B. (2010) · Computer Physics Communications · doi:10.1016/j.cpc.2010.04.004 · Cited by 14

Reducing the influence of tiny normwise relative errors on performance profiles

Dingle, N. J., & Higham, N. J. (2013) · ACM Transactions on Mathematical Software · doi:10.1145/2491491.2491494 · Cited by 14

Fast Exponential Time Integration for Pricing Options in Stochastic Volatility Jump Diffusion Models

Pang, H., & Sun, H. (2014) · East Asian Journal on Applied Mathematics · doi:10.4208/eajam.280313.061013a · Cited by 14

Partial self-consistency and analyticity in many-body perturbation theory: Particle number conservation and a generalized sum rule

Karlsson, D., & van Leeuwen, R. (2016) · Physical review. B./Physical review. B · doi:10.1103/physrevb.94.125124 · Cited by 14

On the exponential of semi-infinite quasi-Toeplitz matrices

Bini, D. A., & Meini, B. (2018) · Numerische Mathematik · doi:10.1007/s00211-018-1006-y · Cited by 14

A Krylov Subspace Method for the Approximation of Bivariate Matrix Functions

Kreßner, D. (2019) · Springer INdAM series · doi:10.1007/978-3-030-04088-8_10 · Cited by 15

The largest eigenvalue distribution of the laguerre unitary ensemble

Lyu, S., & Chen, Y. (2017) · Acta Mathematica Scientia · doi:10.1016/s0252-9602(17)30013-9 · Cited by 14

Computing matrix functions

Higham, N. J., & Al-Mohy, A. H. (2010) · Acta Numerica · doi:10.1017/s0962492910000036 · Cited by 104

4. Techniques for General Functions

Higham, N. J. (2008) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9780898717778.ch4

Condition Estimation for Matrix Functions via the Schur Decomposition

Mathias, R. (1995) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/s0895479893244389 · Cited by 21

Algorithms for Matrix Functions and their Frechet Derivatives and Condition Numbers

Relton, S. D. (2014) · MIMS EPrints (University of Southampton) · Cited by 1

Condition numbers for functions of matrices

Gohberg, I., & Koltracht, I. (1993) · Applied Numerical Mathematics · doi:10.1016/0168-9274(93)90114-7 · Cited by 4