Project outcomes

WP1 – Mathematical tools: matrix computations and matrix equations and inequations solving
WP1, Subactivity 1.1 – Equations and inequations solving in abstract algebraic structures
1. Miroslav Ćirić, Jelena Ignjatović, Predrag Stanimirović, Outer inverses in semigroups belonging to the prescribed Green’s equivalence classes, SEMIGROUP FORUM – submitted for publication.
WP1, Subactivity 1.2 – Developing theory and algorithms for solving systems of matrix equations and inequations
2. Stefan Stanimirović, Ivana Micić, On the solvability of weakly linear systems of fuzzy relation equations, INFORMATION SCIENCES 607 (2022) 670–687, https://doi.org/10.1016/j.ins.2022.05.111
3. W. Jiang, C.-L. Lin, V.N. Katsikis, S.D. Mourtas, P.S. Stanimirović, T.E.Simos, Zeroing neural network approaches based on direct and indirect solutions to the Yang-Baxter-like matrix equation, MATHEMATICS 10(11) (2022) 1950; https://doi.org/10.3390/math10111950
4. T. E. Simos, V.N. Katsikis, S.D. Mourtas, P.S. Stanimirović, Unique non-negative definite solution of the time-varying algebraic Riccati equations with applications to stabilization of LTV system, MATHEMATICS AND COMPUTERS IN SIMULATION 202 (2022), 164-180. https://doi.org/10.1016/j.matcom.2022.05.033
5. D. Gerontitis, R. Behera, Y. Shi, P. S. Stanimirović, A robust noise tolerant zeroing neural network for solving time-varying linear matrix equations, NEUROCOMPUTING 508 (2022) 254-274. https://doi.org/10.1016/j.neucom.2022.08.036
6. A. Kumar, D. Mosić, P. S. Stanimirović, G. Singh, L. A. Kazakovtsev, Commuting outer inverse-based solutions to the Yang–Baxter-like matrix equation, MATHEMATICS 10(15) (2022) 2738, https://doi.org/10.3390/math10152738
7. P.S. Stanimirović, S.D. Mourtas, V.N. Katsikis, L.A. Kazakovtsev, V.N. Krutikov, Recurrent neural network models based on optimization methods, MATHEMATICS 10(22) (2022) 4292; https://doi.org/10.3390/math10224292
8. Siqi Liang, Bo Peng, Predrag S. Stanimirović, Long Jin, Design, analysis, and application of projected k-winner-take-all network, INFORMATION SCIENCES 621 (2023) 74–87, https://doi.org/10.1016/j.ins.2022.11.090
WP1, Subactivity 1.3 – Developing theory and algorithms for matrix factorizations and computing generalized inverses
9. Theodore E. Simos, Vasilios N. Katsikis, Spyridon D. Mourtas, Predrag S. Stanimirović, Dimitris Gerontitis, A higher-order zeroing neural network for pseudoinversion of an arbitrary time-varying matrix with applications to mobile object localization, INFORMATION SCIENCES 600 (2022) 226–238, https://doi.org/10.1016/j.ins.2022.03.094
10. Ivan Kyrchei, Dijana Mosić, Predrag S. Stanimirović, Representations of quaternion W-MPCEP, W-CEPMP and W-MPCEPMP inverses, ADVANCES IN APPLIED CLIFFORD ALGEBRAS (2022) 32:35, https://doi.org/10.1007/s00006-022-01217-z
11. R. Behera, G. Maharana, J.K. Sahoo, P.S. Stanimirović, Characterizations of the Weighted Core-EP Inverses, BULLETIN OF THE IRANIAN MATHEMATICAL SOCIETY (2022), https://doi.org/10.1007/s41980-022-00715-x
12. V. Stanojević, L. Kazakovtsev, P.S. Stanimirović, N. Rezova, G. Shkaberina, Calculating the Moore–Penrose generalized inverse on massively parallel systems, ALGORITHMS, 2022, 15(10), 348, https://doi.org/10.3390/a15100348
WP2 – Semantics and representations of WFAs
WP2, Subactivity 2.1 – Semantics and representations of WFAs over semirings
WP2, Subactivity 2.2 – Semantics in the absence of distributivity
WP2, Subactivity 2.3 – Coalgebraic semantics for WFAs
WP3 – Simulation and bisimulation algorithms
WP3, Subactivity 3.1 – Developing theory and algorithms for testing the existence and computing simulations and bisimulations
13. Miroslav Ćirić, Jelena Ignjatović, Predrag Stanimirović, Bisimulations for weighted finite automata over semirings, SOFT COMPUTING – submitted for publication.
WP3, Subactivity 3.2 – Developing theory and algorithms for testing the existence and computing approximate simulations and bisimulations
14. Ivana Micić, Zorana Jančić, Stefan Stanimirović, Computation of solutions to certain nonlinear systems of fuzzy relation inequations, in: D. Poulakis, G. Rahonis (eds.), Algebraic Informatics, 9th International Conference, CAI 2022, Thessaloniki, Greece, 2022. Proceedings. LECTURE NOTES IN COMPUTER SCIENCE vol. 13706 (2022) pp. 192–202, https://doi.org/10.1007/978-3-031-19685-0_14
15. Ivana Micić, Linh Anh Nguyen, Stefan Stanimirović, Characterization and computation of approximate bisimulations for fuzzy automata, FUZZY SETS AND SYSTEMS 442 (2022) 331–350, https://doi.org/10.1016/j.fss.2022.05.003
WP3, Subactivity 3.3 – Transfer of methodology to weighted social networks and many-valued modal logics
16. Ivan Stanković, Miroslav Ćirić, Jelena Ignjatović, Bisimulations for weighted networks with weights in a quantale, FILOMAT – accepted for publication
17. Marko Stanković, Miroslav Ćirić, Jelena Ignjatović, Simulations and bisimulations for fuzzy multimodal logics over Heyting algebras, FILOMAT – accepted for publication
18. Marko Stanković, Miroslav Ćirić, Jelena Ignjatović, Hennessy-Milner type theorems for fuzzy multimodal logics over Heyting algebras, JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING 39 (2-4) (2022) 341–379.
19. Linh Anh Nguyen, Ivana Micić, Stefan Stanimirović, Fuzzy minimax nets, IEEE TRANSACTIONS ON FUZZY SYSTEMS – submitted for publication.
WP4 – Determinization algorithms
WP4, Subactivity 4.1 – Developing theory and algorithms for state reduction and approximate state reduction of WFAs
WP4, Subactivity 4.2 – Developing theory and algorithms for minimization and approximate minimization of WFAs
WP5 – Semantics and representations of WFAs
WP5, Subactivity 5.1 – Developing new methods and algorithms for determinization of WFAs
WP5, Subactivity 5.2 – Developing theory and algorithms for approximate determinization of WFAs
WP5, Subactivity 5.3 – Developing theory and algorithms for canonization of WFAs
WP6 – Semantics and representations of WFAs
WP6, Subactivity 6.1 – Developing theory and algorithms for reconstruction of WFAs
WP6, Subactivity 6.2 – Developing theory and algorithms for reconstruction of WFAs with output
WP6, Subactivity 6.3 – Developing theory and algorithms for learning WFAs