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    Vera Angelova

    Personal Information

    First name, Surname:

    Vera Angelova

    e-mail

    vera.angelova@iict.bas.bg

    Areas of interest:

    Sensitivity and conditioning of problems from Control Theory, Numerical properties of algorithms, Statistics

    Keywords

    Perturbation analysis, Conditioning, Control theory, Statistics

    Biography

    		  

    Employment

    Organization

    Institute of Information and Communication Technologies – Bulgarian Academy of Sciences

     

    City

    Sofia

     

    Region, State or County

     

    Country or location

    Bulgaria

    Employment details

    Department

    Intelligent systems

     

    Role/title

    Associate Professor

     

    Start date

    2010

     

    End date

    Researcher unique identifier(s)
    (ORCID, ResearcherID, etc.):

    0000-0002-6760-826X

    URL for personal website:

    		  

    Education and qualifications

    Year

    Faculty/department – University/institution – Country

    2005

    Assoc. Prof. Institute of Information Technologies – Bulgarian Academy of Sciences – Bulgaria

    1995

    Ph.D. Institute of Informatics – Bulgarian Academy of Sciences – Bulgaria

    Publications

    Angelova, V., Hached, M., Jbilou, K.. Approximate solutions to large nonsymmetric differential Riccati problems with applications to transport theory. Numerical Linear Algebra with Applications, e2272, 27(1), John Wiley & Sons Ltd, 2020, ISSN:1099-1506, DOI:10.1002/nla.2272, 1-17. SJR (Scopus):1.02, JCR-IF (Web of Science):2.109   Q1, не оглавява ранглистата (Web of Science)   Линк

     

    Angelova, V., Hached, M., Jbilou, K.. Sensitivity of the Solution to Nonsymmetric Differential Matrix Riccati Equation. Mathematics, 9, 8, 2021, ISSN:2227-7390, DOI:https://doi.org/10.3390/math9080855, 855-1-855-18. SJR (Scopus):0.538, JCR-IF (Web of Science):2.592   Q1, не оглавява ранглистата (Web of Science)   Линк

     

    Angelova, V.. Non-local perturbation analysis for equation arising in Tree-Like stochastic processes. Advanced Computing in Industrial Mathematics, BGSIAM 2018. Studies in Computational Intelligence, 961, Springer, Cham, 2021, ISBN:978-3-030-71615-8, DOI:10.1007/978-3-030-71616-5_3, 16-25. SJR (Scopus):0.215   Q4 (Scopus)   Линк

     

    Angelova, V., Balabanov, T., Popchev, I.. On the sensitivity estimation of the symmetric matrix Riccati differential equation. Comptes rendus de l’Academie bulgare des Sciences, 75, 11, Prof. Marin Drinov Academic Publishing House, 2022, ISSN:1310-1331, DOI:10.7546/CRABS.2022.11.11, 1638-1646. SJR (Scopus):0.32, JCR-IF (Web of Science):0.19   Q3 (Scopus)   Линк

     

    Angelova, V.. Sensitivity of the nonlinear matrix equation X^p = A + M(B + X^(−1) )^(−1) M*. Advanced Computing in Industrial Mathematics, . BGSIAM 2020. Studies in Computational Intelligence, 1076, Springer, Cham, 2023, ISSN:1860-949X, DOI:10.1007/978-3-031-20951-2_1, 1-11. SJR (Scopus):0.237   Q4 (Scopus)   Линк