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Publications in Math-Net.Ru |
Citations |
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2024 |
| 1. |
T. V. Yakovleva, “Statistical distribution of the quasi-harmonic signal’s phase: basics of theory and computer simulation”, Computer Research and Modeling, 16:2 (2024), 287–297  |
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2023 |
| 2. |
T. V. Yakovleva, N. S. Kulberg, D. V. Leonov, “Estimation of the size of structural formations in ultrasound imaging through statistical analysis of the echo signal”, Dokl. RAN. Math. Inf. Proc. Upr., 509 (2023), 87–93  ; Dokl. Math., 107:1 (2023), 72–76 |
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2021 |
| 3. |
T. V. Yakovleva, “Features of the statistical distribution of a quasi-harmonic signal phase”, Dokl. RAN. Math. Inf. Proc. Upr., 497 (2021), 35–37  ; Dokl. Math., 103:2 (2021), 95–97  |
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2020 |
| 4. |
T. V. Yakovleva, “Stable character of the rice statistical distribution: the theory and application in the tasks of the signals' phase shift measuring”, Computer Research and Modeling, 12:3 (2020), 475–485 |
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2018 |
| 5. |
M. S. Usanov, N. S. Kulberg, T. V. Yakovleva, S. P. Morozov, “Determination of CT dose by means of noise analysis”, Computer Research and Modeling, 10:4 (2018), 525–533 |
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| 6. |
T. V. Yakovleva, “Signal and noise calculation at Rician data analysis by means of combining maximum likelihood technique and method of moments”, Computer Research and Modeling, 10:4 (2018), 511–523 |
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2017 |
| 7. |
T. V. Yakovleva, “Determining the phase shift of quasiharmonic signals through envelope analysis”, Computer Optics, 41:6 (2017), 950–956 |
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| 8. |
T. V. Yakovleva, “Signal and noise parameters’ determination at rician data analysis by method of moments of lower odd orders”, Computer Research and Modeling, 9:5 (2017), 717–728 |
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2016 |
| 9. |
T. V. Yakovleva, “Theoretical substantiation of the mathematical techniques for joint signal and noise estimation at rician data analysis”, Computer Research and Modeling, 8:3 (2016), 445–473 |
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2015 |
| 10. |
T. V. Yakovleva, “Analytical solution and computer simulation of the task of rician distribution’s parameters in limiting cases of large and small values of signal-to-noise ratio”, Computer Research and Modeling, 7:2 (2015), 227–242 |
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2014 |
| 11. |
T. V. Yakovleva, “Review of MRI processing techniques and elaboration of a new two-parametric method of moments”, Computer Research and Modeling, 6:2 (2014), 231–244 |
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| 12. |
T. V. Yakovleva, “Conditions of Rice statistical model applicability and estimation of the Rician signal's parameters by maximum likelihood technique”, Computer Research and Modeling, 6:1 (2014), 13–25 |
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| 13. |
T. V. Yakovleva, N. S. Kulberg, “Mathematical statistics methods as a tool of two-parametric magnetic-resonance image analysis”, Inform. Primen., 8:3 (2014), 79–89 |
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| 14. |
T. V. Yakovleva, N. S. Kulberg, “Two-parametric analysis of magnetic-resonance images by the maximum likelihood technique in comparison with the one-parametric approximation”, Sistemy i Sredstva Inform., 24:3 (2014), 92–109 |
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