Estimation of the Variance of a Random Signal with an Unknown Frequency Bandwidth
We consider the problem of estimating the variance of a Gaussian stationary stochastic signal with a regular spectral density and a priori unknown frequency bandwidth. Two methods for overcoming an a priori uncertainty are proposed, namely, the quasi-likelihood algorithm and the joint maximum-likeli...
Saved in:
| Published in | Radiophysics and quantum electronics Vol. 65; no. 11; pp. 862 - 875 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.04.2023
Springer Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | We consider the problem of estimating the variance of a Gaussian stationary stochastic signal with a regular spectral density and a priori unknown frequency bandwidth. Two methods for overcoming an a priori uncertainty are proposed, namely, the quasi-likelihood algorithm and the joint maximum-likelihood estimation of all unknown parameters. The structural schemes are developed and the estimation characteristics are found for the synthesized algorithms. The estimation-accuracy loss because of the a priori ignorance of the spectral-density width of a useful signal are determined. |
|---|---|
| AbstractList | We consider the problem of estimating the variance of a Gaussian stationary stochastic signal with a regular spectral density and a priori unknown frequency bandwidth. Two methods for overcoming an a priori uncertainty are proposed, namely, the quasi-like2ihood algorithm and the joint maximum-likelihood estimation of all unknown parameters. The structural schemes are developed and the estimation characteristics are found for the synthesized algorithms. The estimation-accuracy loss because of the a priori ignorance of the spectral-density width of a useful signal are determined. We consider the problem of estimating the variance of a Gaussian stationary stochastic signal with a regular spectral density and a priori unknown frequency bandwidth. Two methods for overcoming an a priori uncertainty are proposed, namely, the quasi-likelihood algorithm and the joint maximum-likelihood estimation of all unknown parameters. The structural schemes are developed and the estimation characteristics are found for the synthesized algorithms. The estimation-accuracy loss because of the a priori ignorance of the spectral-density width of a useful signal are determined. |
| Audience | Academic |
| Author | Turbin, M. M. Titov, K. D. Korchagin, Yu. E. |
| Author_xml | – sequence: 1 givenname: Yu. E. surname: Korchagin fullname: Korchagin, Yu. E. email: korchagin@phys.vsu.ru organization: Voronezh State University – sequence: 2 givenname: M. M. surname: Turbin fullname: Turbin, M. M. organization: Voronezh State University – sequence: 3 givenname: K. D. surname: Titov fullname: Titov, K. D. organization: Voronezh State University |
| BookMark | eNp9kE1LAzEURYNUsFb_gKuA66kvH83MLGtpVSiIH3Ub0kymTW2Tmkwp8-9NHcGdZPFI3j3hci5Rz3lnELohMCQA-V0khHCSAWUZASpo1p6hPhnlLCsJhR7qAzCWFZyzC3QZ4wYgYbzoo5dpbOxONdY77GvcrA3-UMEqp83prvCrcpXf4Te7cmqLj7ZZY-Xwwn06f3R4FszXwTjd4vuUO9qqWV-h81pto7n-nQO0mE3fJ4_Z_PnhaTKeZ5pB2WRLVrBK1fWo5FyLEhhfQs1MRTmH3ABRrCo5pJUGVdFySXJNGKelyEEILZZsgG67f_fBpw6xkRt_CKlklLQQghOWF5BSwy61Ulsjrat9E5ROpzI7q5PE2qb3cS5EQQQlPAG0A3TwMQZTy31IgkIrCciTa9m5lsm1_HEt2wSxDoop7FYm_HX5h_oGNniCAQ |
| Cites_doi | 10.1109/IWASI.2017.7974238 10.1134/S1069351319040098 10.1134/S106377102101005X 10.1109/TGRS.2007.893817 10.1109/IMTC.1999.776786 10.1186/s43020-019-0001-5 10.1016/B978-012265655-2/50002-7 10.1134/S1028334X1904007X 10.1007/978-1-4613-8643-8 10.1109/TIM.2019.2896371 |
| ContentType | Journal Article |
| Copyright | Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. COPYRIGHT 2023 Springer |
| Copyright_xml | – notice: Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. – notice: COPYRIGHT 2023 Springer |
| DBID | AAYXX CITATION 7SP 7U5 8FD H8D L7M |
| DOI | 10.1007/s11141-023-10262-y |
| DatabaseName | CrossRef Electronics & Communications Abstracts Solid State and Superconductivity Abstracts Technology Research Database Aerospace Database Advanced Technologies Database with Aerospace |
| DatabaseTitle | CrossRef Aerospace Database Solid State and Superconductivity Abstracts Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts |
| DatabaseTitleList | Aerospace Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Physics |
| EISSN | 1573-9120 |
| EndPage | 875 |
| ExternalDocumentID | A766816214 10_1007_s11141_023_10262_y |
| GroupedDBID | -54 -5F -5G -BR -EM -Y2 -~C -~X .86 .VR 06D 0R~ 0VY 1N0 1SB 2.D 28- 29P 29~ 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 4.4 406 408 409 40D 40E 5QI 5VS 642 67Z 6NX 6TJ 8FE 8FG 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AABYN AAFGU AAHNG AAIAL AAJKR AANZL AAPBV AARHV AARTL AATNV AATVU AAUYE AAWCG AAYFA AAYIU AAYQN AAYTO ABBBX ABBXA ABDBF ABDZT ABECU ABFGW ABFTV ABHLI ABHQN ABJCF ABJNI ABJOX ABKAS ABKCH ABKTR ABMNI ABMQK ABNWP ABPTK ABQBU ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABWNU ABXPI ACBMV ACBRV ACBXY ACBYP ACGFS ACHSB ACHXU ACIGE ACIPQ ACIWK ACKNC ACMDZ ACMLO ACNCT ACOKC ACOMO ACTTH ACVWB ACWMK ADHHG ADHIR ADIMF ADINQ ADJSZ ADKNI ADKPE ADMDM ADOXG ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEEQQ AEFIE AEFTE AEGAL AEGNC AEGXH AEJHL AEJRE AEKMD AENEX AEOHA AEPYU AESKC AESTI AETLH AEVLU AEVTX AEXYK AEYGD AFEXP AFFNX AFGCZ AFGFF AFKRA AFLOW AFNRJ AFQWF AFWTZ AFZKB AGAYW AGDGC AGGBP AGGDS AGJBK AGMZJ AGQMX AGWIL AGWZB AGYKE AHAVH AHBYD AHSBF AHYZX AIAKS AIIXL AILAN AIMYW AITGF AJBLW AJDOV AJRNO AKQUC ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARMRJ ASPBG AVWKF AXYYD AZFZN B-. B0M BA0 BBWZM BDATZ BENPR BGLVJ BGNMA CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 EAD EAP EBLON EBS EIOEI EJD EMK EPL ESBYG ESX FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GPTSA GQ6 GQ7 GQ8 GXS HCIFZ HF~ HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I-F IAO IHE IJ- IKXTQ ITC IWAJR IXC IXD IXE IZIGR IZQ I~X I~Z J-C JBSCW JCJTX JZLTJ KDC KOV KOW L6V LAK LLZTM M4Y M7S MA- N2Q NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P62 P9T PF0 PT4 PT5 PTHSS QOK QOS R4E R89 R9I RHV RIG RNI RNS ROL RPX RSV RZC RZE RZK S16 S1Z S26 S27 S28 S3B SAP SCLPG SDH SDM SGB SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPH SPISZ SRMVM SSLCW STPWE SZN T13 T16 TEORI TN5 TSG TSK TSV TUC TUS U2A UG4 UNUBA UOJIU UTJUX UZXMN VC2 VFIZW VOH W23 W48 WK8 XU3 YLTOR Z7R Z7X Z7Z Z83 Z88 Z8M Z8R Z8T Z8W Z92 ZMTXR ~8M ~A9 ~EX AACDK AAEOY AAJBT AASML AAYXX ABAKF ACAOD ACDTI ACZOJ AEFQL AEMSY AFBBN AGQEE AGRTI AIGIU CITATION 7SP 7U5 8FD H8D L7M |
| ID | FETCH-LOGICAL-c309t-b383daff5944c69034b0f3ed24407e01a3d9404c6c0ad29b17c1342967066c6b3 |
| IEDL.DBID | AGYKE |
| ISSN | 0033-8443 |
| IngestDate | Thu Oct 10 22:09:01 EDT 2024 Tue Apr 09 06:03:05 EDT 2024 Thu Sep 12 16:52:22 EDT 2024 Sat Dec 16 12:03:42 EST 2023 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 11 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c309t-b383daff5944c69034b0f3ed24407e01a3d9404c6c0ad29b17c1342967066c6b3 |
| PQID | 2866413780 |
| PQPubID | 2034513 |
| PageCount | 14 |
| ParticipantIDs | proquest_journals_2866413780 gale_infotracacademiconefile_A766816214 crossref_primary_10_1007_s11141_023_10262_y springer_journals_10_1007_s11141_023_10262_y |
| PublicationCentury | 2000 |
| PublicationDate | 2023-04-01 |
| PublicationDateYYYYMMDD | 2023-04-01 |
| PublicationDate_xml | – month: 04 year: 2023 text: 2023-04-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York |
| PublicationTitle | Radiophysics and quantum electronics |
| PublicationTitleAbbrev | Radiophys Quantum El |
| PublicationYear | 2023 |
| Publisher | Springer US Springer Springer Nature B.V |
| Publisher_xml | – name: Springer US – name: Springer – name: Springer Nature B.V |
| References | A. D’Alessandro, G. Vitale, S. Scudero, et al., in: 7th IEEE Int. Workshop on Advances in Sensors and Interfaces (IWASI). June 15–16, 2017, pp. 159–164. https://doi.org/10.1109/IWASI.2017.7974238 P. Welander, M. Barmatz, and I. Hahn, in: Proc. 16th IEEE Instrumentation and Measurement Technology Conf., May 24–26, 1999, Venice, Italy, Vol. 1, pp. 413–416. https://doi.org/10.1109/IMTC.1999.776786 El-SheimyNYoussefASatell. Navig.20201210.1186/s43020-019-0001-5 DevroyeLNon-Uniform Random Variate Generation1986BerlinSpringer-Verlag10.1007/978-1-4613-8643-80593.65005 SobolevGASeismic Noise2014MoscowNauka i Obrazovanie[in Russian] IbrahimAEltawilANaYEl-TawilSIEEE Trans. Instrum. Meas.20206925735842020ITIM...69..573I10.1109/TIM.2019.2896371 G. A. Sobolev and N. A. Zakrzhevskaya, Izv., Phys. Solid Earth, 55, No. 4, 529–547 (2019). https://doi.org/10.1134/S1069351319040098 KulikovEITrifonovAPEstimation of Signal Parameters against Noise Background1978MoscowSovetskoe Radio[in Russian] TikhotskySAPresnovDASobisevichALShurupASAcoust. Phys.202167191992021APhy...67...91T10.1134/S106377102101005X LazorenkoOVChernogorLFRadiofiz. Radioastron.20081342703222008RPRA...13..270L TikhonovVIStatistical Radio Engineering1982MoscowRadio i Svyaz’[in Russian] KulikovEIMethods for Measuring Random Processes1986MoscowRadio i Svyaz’[in Russian] Yu.E.Korchagin and M. M.Turbin, Radiotekhnika, № 3, 12–19 (2018). TikhonovVINechaevEPParfenovVIDetection of Stochastic Signals with Unknown Parameters1991VoronezhVoronezh State Univ[in Russian] A.P.Trifonov, O.V.Chernoyarov, and D. N. Shepelev, Radiotekhnika, № 4, 16–22 (2009). V. I. Mudrov and V. L.Kushko, Methods for Processing Measurements. Quasi-Likelihood Estimates, Radio i Svyaz’, Moscow (1983). BykovVVDigital Simulation in Statistical Radio Engineering1971MoscowSovetskoe Radio[in Russian] A.P.Trifonov and S.P.Alekseenko, Izv. Vyssh. Uchebn. Zaved., Radioélektron., 37, No. 11, 10–18 (1994). PetkovPCyber. Inf. Technol.201010263140 DarawankulAJohnsonJTIEEE Trans. Geosci. Remote Sens.2007455119812062007ITGRS..45.1198D10.1109/TGRS.2007.893817 SobolevGADokl. Earth. Sci.201948523954002019DokES.485..395S10.1134/S1028334X1904007X TrifonovAPZakharovAVChernoyarovOVRadiotekh. Élektron.1996411012071210 FranceschettiGRiccioDScattering, Natural Surfaces, and Fractals, Academic PressCambridge200710.1016/B978-012265655-2/50002-71152.78301 GA Sobolev (10262_CR3) 2019; 485 A Ibrahim (10262_CR10) 2020; 69 G Franceschetti (10262_CR20) 2007 10262_CR8 VI Tikhonov (10262_CR17) 1991 A Darawankul (10262_CR21) 2007; 45 N El-Sheimy (10262_CR9) 2020; 1 10262_CR11 L Devroye (10262_CR23) 1986 VV Bykov (10262_CR22) 1971 GA Sobolev (10262_CR5) 2014 10262_CR4 VI Tikhonov (10262_CR16) 1982 EI Kulikov (10262_CR1) 1986 EI Kulikov (10262_CR2) 1978 SA Tikhotsky (10262_CR6) 2021; 67 10262_CR15 P Petkov (10262_CR7) 2010; 10 OV Lazorenko (10262_CR12) 2008; 13 10262_CR13 10262_CR19 10262_CR18 AP Trifonov (10262_CR14) 1996; 41 |
| References_xml | – volume: 10 start-page: 31 issue: 26 year: 2010 ident: 10262_CR7 publication-title: Cyber. Inf. Technol. contributor: fullname: P Petkov – ident: 10262_CR8 doi: 10.1109/IWASI.2017.7974238 – volume-title: Estimation of Signal Parameters against Noise Background year: 1978 ident: 10262_CR2 contributor: fullname: EI Kulikov – ident: 10262_CR4 doi: 10.1134/S1069351319040098 – volume: 41 start-page: 1207 issue: 10 year: 1996 ident: 10262_CR14 publication-title: Radiotekh. Élektron. contributor: fullname: AP Trifonov – volume: 67 start-page: 91 issue: 1 year: 2021 ident: 10262_CR6 publication-title: Acoust. Phys. doi: 10.1134/S106377102101005X contributor: fullname: SA Tikhotsky – volume-title: Digital Simulation in Statistical Radio Engineering year: 1971 ident: 10262_CR22 contributor: fullname: VV Bykov – volume: 45 start-page: 1198 issue: 5 year: 2007 ident: 10262_CR21 publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2007.893817 contributor: fullname: A Darawankul – volume-title: Seismic Noise year: 2014 ident: 10262_CR5 contributor: fullname: GA Sobolev – volume-title: Methods for Measuring Random Processes year: 1986 ident: 10262_CR1 contributor: fullname: EI Kulikov – ident: 10262_CR11 doi: 10.1109/IMTC.1999.776786 – volume: 1 start-page: 2 year: 2020 ident: 10262_CR9 publication-title: Satell. Navig. doi: 10.1186/s43020-019-0001-5 contributor: fullname: N El-Sheimy – volume-title: Detection of Stochastic Signals with Unknown Parameters year: 1991 ident: 10262_CR17 contributor: fullname: VI Tikhonov – year: 2007 ident: 10262_CR20 publication-title: Cambridge doi: 10.1016/B978-012265655-2/50002-7 contributor: fullname: G Franceschetti – ident: 10262_CR19 – ident: 10262_CR18 – volume: 485 start-page: 395 issue: 2 year: 2019 ident: 10262_CR3 publication-title: Dokl. Earth. Sci. doi: 10.1134/S1028334X1904007X contributor: fullname: GA Sobolev – volume-title: Non-Uniform Random Variate Generation year: 1986 ident: 10262_CR23 doi: 10.1007/978-1-4613-8643-8 contributor: fullname: L Devroye – volume-title: Statistical Radio Engineering year: 1982 ident: 10262_CR16 contributor: fullname: VI Tikhonov – volume: 69 start-page: 573 issue: 2 year: 2020 ident: 10262_CR10 publication-title: IEEE Trans. Instrum. Meas. doi: 10.1109/TIM.2019.2896371 contributor: fullname: A Ibrahim – volume: 13 start-page: 270 issue: 4 year: 2008 ident: 10262_CR12 publication-title: Radiofiz. Radioastron. contributor: fullname: OV Lazorenko – ident: 10262_CR15 – ident: 10262_CR13 |
| SSID | ssj0010048 |
| Score | 2.3005874 |
| Snippet | We consider the problem of estimating the variance of a Gaussian stationary stochastic signal with a regular spectral density and a priori unknown frequency... |
| SourceID | proquest gale crossref springer |
| SourceType | Aggregation Database Publisher |
| StartPage | 862 |
| SubjectTerms | Algorithms Analysis Astronomy Astrophysics and Astroparticles Density Distribution (Probability theory) Hadrons Heavy Ions Lasers Mathematical and Computational Physics Maximum likelihood estimation Nuclear Physics Observations and Techniques Optical Devices Optics Photonics Physics Physics and Astronomy Quantum Optics Random signals Theoretical Variance |
| Title | Estimation of the Variance of a Random Signal with an Unknown Frequency Bandwidth |
| URI | https://link.springer.com/article/10.1007/s11141-023-10262-y https://www.proquest.com/docview/2866413780 |
| Volume | 65 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3Nb9MwFH_aWiGxAx8d0zpG5QMSB0iVxI6THFNoqTaBBLSoO1mO7UA1LZ3aTKj76_ecD8pWdugxsmUrfj-_D_u9nwHe-r6knpLcycI4c5gJ7DMvMnaoCbg2iAKqbO3wl698PGVns2C2qeMuk92bG8lSUW9q3dBzx8jXt6lUPved9T60A0v41YJ28vnifPj38sCismJjpE7EGK1rZf4_yj179FArb12PllZn9BwmTe1OlWxy2b8p0r663aZy3OWHXsCz2gslSQWbl7Bn8g4c_MNN2IEnZW6oWh3CtyGqgarCkSwygh4j-YkRtoWL_Zbku8z14or8mP-yg9qTXSJzMs3teV1ORssqW3tNBtjvz1wXv1_BdDScfBw79UsMjqJuXDgpxrFaZlkQM6YwnqYsdTNqNPoGbmhcT1IdMxeblCu1H6deqDyKlo6H6NEontIjaOWL3BwDyThqAKNjjNwMk5qj_0N1oAMeyjQKMt6F9408xHVFuCE21Mp2yQQumSiXTKy78M6KTNjdWCylknVRAc5lea1EEnIeeRxh0oXTRqqi3qYr4UecoxUPI7cLHxopbZofn_dkt-6v4al9pr7K-DmFVrG8MW_QmSnSHoJ38Gkw6tUg7sH-1E_uAA1n6k4 |
| link.rule.ids | 315,786,790,27955,27956,41114,41556,42183,42625,52144,52267 |
| linkProvider | Springer Nature |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT9wwEB5RUNVyqCgtYoGCD0gcaKTEdpzkuFSsFthFKhDEzXL8gD2QrXZTVfvvGefBUtoeerRs2dI8PDP2NzMAh5QqFmklApdkLuA29m1eVBYwGwtjUQqY9rnD40sxzPn5XXzXJoXNO7R79yVZ39TLZDd03TH0pR5LRQUNFm9gzddT90C-nPaf_w68UDbFGFmQcs7aVJm_7_GbOXp9Kf_xO1obncEGfGi9RdJv2PsRVmy5Cesvaghuwtsaw6nnn-D7Kaprk4lIpo6gZ0duMRL2bPVjRa5UaaaP5Hpy7zf1L7BElSQv_btaSQazBlW9ICe47tfEVA-fIR-c3nwbBm3HhECzMKuCAuNNo5yLM841xr2MF6Fj1qANDxMbRoqZjIc4pUNlaFZEiY4YWiSRoOehRcG2YLWclnYbiBOoqdZkGGFZroxAP4WZ2MQiUUUaO9GD445w8kdTGEMuSyB7Mksks6zJLBc9OPK0lV5rqpnSqgX_41m-_pTsJ0KkkaAR78FeR37ZqtNc0lQItLZJGvbga8eS5fS_z935v-UH8G54Mx7J0dnlxS68963lG5TOHqxWs5_2CzogVbFfy9sTUPzOng |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT9wwEB7xUCt6qCgUdQsFHyr1ABGJ7TjJcduy4tGi8tiKm-X4QTmQRUuqav89M0m2S6EcOEa2bGkemRnPfDMAHzk3IrFGRSErQiR9SmNeTBEJnyrnUQqEJezw92O1P5SHF-nFPRR_U-0-TUm2mAbq0lTVuzcu7M6Ab-jGYxjMqa6KKx5N5mGRTCPJ-JD3_-YRSEDbxowiyqUUHWzm_2f8Y5oe_qAfZUobAzRYhted58j6LavfwJyvVuDVvX6CK_Ciqee0t6twsoeq26IS2Sgw9PLYT4yKicX0bdipqdzomp1dXdKh9BrLTMWGFb2xVWwwbiusJ-wz7vtz5epfb2E42Dv_sh910xMiK-KijkqMPZ0JIS2ktBgDC1nGQXiH9jzOfJwY4QoZ45KNjeNFmWQ2EWidVIZeiFWlWIOFalT5d8CCQq31rsBoy0vjFPoswqUuVZkp8zSoHmxPCadv2iYZetYOmciskcy6IbOe9OAT0VaTBtVjY00HBMC7qBeV7mdK5YniiezBxpT8ulOtW81zpdDyZnncg50pS2bLT9_7_nnbt-Dlj68D_e3g-GgdlmjKfFuwswEL9fi3_4C-SF1uNuJ2B6lT0uM |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Estimation+of+the+Variance+of+a+Random+Signal+with+an+Unknown+Frequency+Bandwidth&rft.jtitle=Radiophysics+and+quantum+electronics&rft.au=Korchagin%2C+Yu.+E.&rft.au=Turbin%2C+M.+M.&rft.au=Titov%2C+K.+D.&rft.date=2023-04-01&rft.pub=Springer+US&rft.issn=0033-8443&rft.eissn=1573-9120&rft.volume=65&rft.issue=11&rft.spage=862&rft.epage=875&rft_id=info:doi/10.1007%2Fs11141-023-10262-y&rft.externalDocID=10_1007_s11141_023_10262_y |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0033-8443&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0033-8443&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0033-8443&client=summon |