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The paper describes two algorithms for the formation of ensembles of signals from the PM, analyzes the noise immunity of receiving signals from the PM, and discusses in detail issues related to the selection of ECC parameters for low-speed communication systems that can ensure high reliability of message reception and their high spectral efficiency. It is shown that, in contrast to high-speed communication systems, in which two-dimensional AS with quadrature-amplitude modulation and ECCs with MACD are used for message transmission, in the studied low-speed systems, the optimal choice of their parameters allows their energy and spectral efficiency to be very close to the limiting ones - those that have the "perfect" Shannon system. It is also shown that the ECC used in these systems can have a relatively small length and its implementation is quite simple in technical terms. 2. Kotel'nikov V.A. Teoriya potentsial'noy pomekhoustoychivosti. (The theory of potential noise immunity) Moscow: State Energy Publishing House. 1956. p. 152 3. John G. Proakis. Digital communications/ New York : McGraw-Hill, 1989. p. 608 4. Slepian D. Permutation modulation. Proc. IEEE, vol. 53, Mar. 1965. pp. 228-236 5. Bykhovskiy M.A. Giperfazovaya modulyatsiya – optimal'nyy metod peredachi soobshcheniy v gaussovskikh kanalakh svyazi. (Hyperphase modulation is the optimal method for transmitting messages in Gaussian communication channels) M.: Tekhnosfera, 2018. p. 310 6. W. Wesley Peterson and E. J. Weldon, Jr. Error-Correcting Codes, Second Edition, The MIT Press, 1972. p. 576 7. A.A. Frolov, V.V. Zyablov, Granitsy minimal'nogo kodovogo rasstoyaniya dlya nedvoichnykh kodov na dvudol'nykh grafakh, Problemy peredachi informatsii, (Boundaries of the minimum code distance for nonbinary codes on bipartite graphs, Problems of Information Transmission) 2011, vypusk 4, pp. 27-42 8. Frolov A.A. Korrektiruyushchiye svoystva nedvoichnykh kodov s maloy plotnost'yu proverok. Correcting properties of non-binary codes with low density of checks). Dissertation for the scientific degree of fis.-mat. sciences. IPPI named after Kharkevich. RAS, 2012. p. 117 9. Osipchuk S.A. Povysheniye informatsionnoy effektivnosti besprovodnykh sistem peredachi na osnove pereraspredeleniya resursov kanala svyazi. KPI, (Improving the information efficiency of wireless transmission systems based on reallocation of communication channel resources). KPI, Dissertation for the degree of candidate of technical sciences, Kiev, 2015 p. 182 10. Uryvsky L., Osypchuk S. The analytical description of regular LDPS codes correcting ability. Institute of Telecommunication Systems National Technical University of Ukraine “Kyiv Polytechnic Institute”. Transport and Telecommunication Vol. 15, ¹ 3, 2014 11. Bykhovskiy M.A. Metod formirovaniya mnogochastotnykh shirokopolosnykh signalov i vozmozhnosti ikh primeneniya v sistemakh svyazi. (Method of formation of the multifrequency broadband signals and possibilities of their application in communication systems)//Cifrovaja obrabotka signalov (Digital signal processing), 2019, no. 1, pp. 10–13.
-mail:vashkevich@bsuir.by
2.T. Gulzow, A. Engelsberg, and U. Heute, "Comparison of a discrete wavelet transformation and a nonuniform polyphase filterbank applied to spectral-subtraction speech enhancement," Signal processing, vol. 64, no. 1, pp. 5-19, 1998. 3.J. M. Kates and K. H. Arehart, "Multichannel dynamic-range compression using digital frequency warping," EURASIP journal on advances in signal processing, vol. 2005, no. 18, pp. 1-12, 2005. 4. M.I. Vashkevich, I.S. Azarov, and A.A. Petrovsky, “Cosine-modulated filter banks with all-pass transform in hearing aid design”. M.: Hotline Telecom, 2014, p. 210. (in Russian). 5. M.I. Vashkevich and I.S. Azarov, " Comparison of time-frequency transforms: Fourier analysis, wavelets and allpass transformed filter banks," Digital signal processing, no. 2, pp. 13-26, 2020. (in Russian) 6. J. O. Smith and J. S. Abel, "Bark and ERB bilinear transforms," IEEE Transactions on speech and Audio Processing, vol. 7, no. 6, pp. 697-708, 1999. 7. P. Vary, "Digital filter banks with unequal resolution," in Short Communication Digest of European Signal Processing Conf.(EUSIPCO), 1980, pp. 41-42. 8. B. Gold, C. M. Rader, Digital processing of signals. McGraw-Hill, 1969, p. 368. 9. E. C. Ifeachor, B. W. Jervis, Digital signal processing: a practical approach. Pearson Education, 2002, p. 992. 10. V. S. Gladky, "Selecting the number of bits per word in transmission of data on process probabilistic characteristics," Automation and Remote Control, no. 3, pp. 159–166, 1973. (in Russian)
2. Gwon T.M. A Polymer Cochlear Electrode Array: Atraumatic Deep Insertion, Tripolar Stimulation, and Long-Term Reliability. 1-st Ed. Springer, 2018. 87 p. doi: https://doi.org./10.1007/978-981-13-0472-9. 3. Djourno A., Eyries C. Auditory prosthesis by means of a distant electrical stimulation of the sensory nerve with the use of an indwelt coiling // Presse Med. 1957. Vol. 65(63). P. 1417. 4. House W.F, Urban J. Long term results of electrode implantation and electronic stimulation of the cochlea of man // Ann Otol Rhinol Laryngol. 1973. Vol. 85. P. 504. 5. House W.F. Cochlear Implants // Ann Otol Rhino Laryngol. 1976. Vol. 85. Suppl. 27. P. 1–93. 6. Doyle J., Doyle D., House W. Electical stimulation of eight nerve deafness // Bulletin of the Los Angeles Neurological Society. 1963. Vol. 28. P. 148-150. 7. Zollner F., Keidel W.D. Gehorvermittlung durch elektrische Erregung des Nervus acusticus [Transmission of hearing by electrical stimulation of the acoustic nerve] // Arch Ohren Nasen Kehlkopfheilkd. 1963. Vol. 181. P. 216-223. doi: 10.1007/BF02103758. 8. Clark G.M., Hallworth R.J., Zdanius K. A ñochlear implant electrode // Journal of Laryngology and Otology. 1975. Vol. 89. P. 787-792. 9. Clark G.M., Tong Y.C., Martin L.F. A multiple channel cochlear implant: an evaluation using open—set CID sentences // Laryngoscope. 1981. Vol. 91. P. 628-634. 10. Kiang N.Y.S., Moxon E.C. Physiological considerations in artificial stimulation of the inner ear. Annals of Otology // Rhinology and Laryngology. 1972. Vol. 81. P. 714-730. 11. Lawrence M., Johnsson L.G. The role of the organ of Corti in auditory nerve stimulation. Annals of Otology // Rhinology and Laryngology. 1973. Vol. 82. P. 464-472. 12. Merzenich M.M., White M.W., Leake P.A., Schindler R.A., Michelson R.P. Further progress in the development of multichannel cochlear implants // Transactions. Section of Otolaryngology. American Academy of Ophthalmology and Otolaryngology. 1977. Vol. 84 (2). P. 181-182. 13. Schuknecht H.F. Lesions of organ of Corti // Transactions American Academy of Ophthalmology and Otolaryngology. 1953. Vol. 57. P. 366-383. 14. Simmons F.B., Epley J.M., Lummis R.C., Guttman N., Frishkopf R.S., Harmon L.D., Zwicker E. Auditory nerve: electrical stimulation in man // Science. 1965. Vol. 148. P. 104-106. 15. Boyle P.J. Electrical Stimulation of the Auditory System. The Human Auditory System Basic Features and Updates on Audiological Diagnosis and Therapy. IntechOpen. 2019. doi:10.5772/intechopen. 16. Bouafif L., Performances Study of a New Speech Coding Strategy with Reduced Channels for Cochlear Implants // The Open Signal Processing Journal. 2009. Vol. 29. P. 29-39. doi: 10.2174/1876825300902010029. 17. Loizou P., Liu X. Improving vowel recognition in noise using the CIS strategy. 29th Annual Neural Prosthesis. Workshop. NIH: Bethesda, MD, USA, 1998. 18. Waibel A., Hanazawa T., Hinton G., Shikano K., Lang K., Phoneme recognition using time-delay neural networks // IEEE Transaction on Acoustic. Speech and Signal Processing. 1989. Vol. 37(3). P. 328-338. 19. Kiefer J., Hohl S., Sturzebecher E., Pfennigdorff T., Gstoettner W. Comparison of Speech Recognition with Different Speech Coding Strategies (SPEAK, CIS, and ACE) and Their Relationship to Telemetric Measures of Compound Action Potentials in the Nucleus CI 24M Cochlear Implant System:Comparacion del reconocimiento del lenguaje utilizando diferentes estrategias (SPEAK, CIS y ACE) y su relacion con mediciones telemetricas de potenciales de accion compuestos, con el sistema de implante coclear nucleus CI24M // Audiology. 2001. Vol. 40 (1). P. 32-42. 20. Swanson B.A. Pitch Perception with Cochlear Implants. PhD thesis. Otolaryngology Eye and Ear Hospital: The University of Melbourne. 2008. URI: http://hdl.handle.net/11343/39587. 21. Psarros C.E., Plant K.L., Lee K., Decker J.A., Whitford L.A., Cowan R.S. Conversion from the SPEAK to the ACE strategy in children using the nucleus 24 cochlear implant system: speech perception and speech production outcomes // Ear and hearing. 2002. Vol. 23(1). P. 18S-27S. 22. Stavros H., Ciorba A., Skarzynski P.H. The Human Auditory System: Basic Features and Updates on Audiological Diagnosis and Therapy. London: BoD–Books on Demand, 2020. doi: http://dx.doi. org/10.5772/intechopen.77713. 23. Manrique M., Huarte A., Morera C., Caballe L., Ramos A., Castillo C., Garcia-Ibanez L., Estrada E., Juan E. Speech perception with the ACE and the SPEAK speech coding strategies for children implanted with the Nucleus cochlear implant // International Journal of Pediatric Otorhinolaryngology. 2005. Vol. 69(12). P. 1667-1674. doi: https://doi.org/10.1016/j.ijporl.2005.03.049. 24. Donaldson G.S., Kreft H.A., Litvak, L. Place-Pitch Eiscrimination of Singleversus Dual-Electrode Stimuli by Cochlear Implant Users // Journal of Acoustic Society of America. 2005. Vol. 118(22). P. 623-626, ISSN 0001-4966. 25. Koch D.B., Osberger M.J., Segal P., Kessler, D. HiResolution and Conventional Sound Processing in the HiResolution Bionic Ear: Using Appropriate Outcome Measures to Assess Speech Recognition Ability // Audiology and Neurotology. 2004. Vol. 9(4). P. 241-223. ISSN 1420-3030. 26. Tichy T., Sovka P., Vondrasek M. ACE Strategy with Virtual Channels // Radioengeneering. 2008. Vol. 17(4). P. 55-61. 27. Wilson B.S., Dorman M.F. Cochlear Implants: Current Designs and Future Possibilities // Journal of Rehabilitation Research and Development. 2008. Vol. 45(5). P. 695-730. ISSN 0748-7711. 28. Choi C.T.M., Hsu C.H. Conditions for Generating Virtual Channels in Cochlear Prosthesis Systems // Annals of Biomedical Engineering. 2009. Vol. 37(3). P. 614-624. ISSN 0090-6964. 29. Choi C.T., Lee Y.H. A review of stimulating strategies for cochlear implants // Cochlear Implant Research Updates. 2012. 16 p.
To assess the degree of influence of trajectory instabilities on the quality of the generated radar images and to determine the optimal value of the synthesis time, the following steps were performed: calculation of the statistical characteristics of trajectory instabilities recorded by onboard sensors during flight for various types of aircraft; flight simulation of aircraft in the presence of trajectory instabilities, taking into account the calculated statistical characteristics; the integration of mathematical models of the flight of the aircraft into the algorithms for forming the radar image, followed by the calculation by the simulation method of the optimal time for synthesizing the aperture, which ensures the best quality of the radar image. To calculate the statistical characteristics of trajectory instabilities, a number of flight experiments were carried out using various types of aircraft: unmanned aerial vehicles of the aircraft type Skywalker 1880 and Phoenix (NPP New Technologies of Telecommunications LLC, St. Petersburg), piloted helicopter Robinson R44, as well as the Il-114ll manned aircraft (JSC NPP Radar mms, St. Petersburg). The registration of flight parameters was carried out on straight sections of the trajectory by the Ublox NEO-M8 SRNS receiver, the data from the output of which were stored at a frequency of 10 Hz in the form of coordinates, speed and altitude readings of the carrier for sub-sequent statistical processing. On the basis of the obtained statistical characteristics, the modeling of trajectory instabilities was carried out, which was carried out by passing white Gaussian noise through a shaping filter, the impulse response of which is calculated on the basis of an autocorrelation function with a given spectral width. The calculation of the value of the optimal synthesis time, which provides the best quality of the radar image, is based on the formation of a radar image, a test scene consisting of a single point reflector with known coordinates typical for the observation conditions of a small-sized high-resolution radar with the subsequent calculation of the resolution along the track range in the width of the response from point reflector. Thus, based on the assessment of the statistical characteristics of trajectory instabilities of various types of unmanned and manned aerial vehicles, as well as the degree of influence of trajectory instabilities on the quality of the generated radar images, a new approach is proposed for estimating the optimal synthesis time in the presence of trajectory instabilities based on the analysis of their statistical characteristics. The inclusion of procedures for evaluating the optimal synthesis time in the algorithms for forming the radar image will ensure the achievement of the maximum permissible quality of the radar image at their are automatically formation on board the carrier while reducing computational costs.
2. Il'in E., Polubekhin A., Savost'yanov V., Samarin O. MBRLS Ku-diapazona dlin radiovoln. Vazhnyj shag k vnedreniyu v sostav bortovogo radioelektronnogo oboru-dovaniya BLA (MBRLS Ku-band radio wavelengths. An important step towards the introduction of UAVs into the avion-ics) // Radioelektronnye tekhnologii, No 3. 2020. pp. 20-25. 3. Kulakova V.I., Nozdrin S.A., Soharev A.YU., Carik D.V. Sistema mikronavigacii dlya podderzhki radiolokatora s sintezirovannoj aperturoj na bortu malogaba-ritnogo BpLA (Micronavi-gation system to support synthetic aperture radar on board a small-size UAV) // Giroskopiya i navi-gaciya. Vol 27. No (107), 2019. pp. 130-146. 4. SHkol'nyj L.A. Radiolokacionnye sistemy vozdushnoj razvedki, deshifriro-vanie radiolo-kacionnyh izobrazhenij (Radar systems of aerial reconnaissance, decoding of radar images). M.: VVIA im. Prof. N.E. ZHukovskogo, 2008. 531 p. 5. Gur'yanov M.A., Prokof'ev A.A. Avtopodbor parametrov sinteza radiolokaci-onnogo izo-brazheniya, poluchennogo s radiolokatora s sintezirovannoj aperturoj (Automatic selection of the synthesis parameters of the radar image obtained from the synthetic aperture radar) // Izve-stiya vuzov. Elektronika. Vol 20, No 2, 2015. pp. 161-167. 6. Lihachev V.P., Pasmurov A.YA. Formirovanie radiolokacionnyh izobrazhenij letatel'nyh apparatov metodom obrashchennogo sintezirovaniya apertury v usloviyah cha-stichnoj kogerentnosti signala (Formation of radar images of aircraft by the method of inverse aperture synthesis under conditions of partial signal coherence) // Radiotekhnika i elektronika, No 3. 1999. pp. 294. 7. Lihachev V.P. Vliyanie sistemy obrabotki signalov RLS s sintezirovannoj aperturoj na harakteristiki izobrazhenij imitiruemyh celej (Influence of the signal processing system of a radar with a synthetic aperture on the characteristics of images of simulated targets) // Trudy 5 Mezhdu-narod-noj NTK «Radiolokaciya, navigaciya, svyaz'». Vol 2. Voronezh: VGU. 1999. pp. 887-895. 8. Mitrofanov D.G., Tkachenko V.P. Issledovaniya parametrov traektornyh nesta-bil'nostej le-tatel'nyh apparatov metodom naturnogo eksperimenta (Research of parameters of trajectory instabil-ities of aircraft by the method of a full-scale experiment) // Izvestiya Rossij-skoj akademii raketnyh i artillerijskih nauk, No 2. 2009. pp. 70-82. 9. Wahl D.E., Eichel P.H., Ghiglia D.C., Jakowatz C.V. Phase Gradient Autofocus – A Ro-bust Tool for High Resolution SAR Phase Correction // IEEE Trans. Aerospace Electron. Syst. No 3, 1994. pp. 827-834. 10. Tihonov V.I. Statisticheskaya radiotekhnika (Statistical radio engineering). M.: Radio i svyaz', 1982. 624 p. 11. Solonina A.I., Klionskij D.M., Merkucheva T.V., Perov S.N. Cifrovaya obra-botka signal-ov i MATLAB (Digital Signal Processing and MATLAB). SPb.: BHV-Peterburg, 2013. 512 p. 12. Lajons R. Digital Signal Processing: Second Edition. M.: «Binom-Press», 2006. 656 p 13. Spravochnik po radiolokacii (Handbook of radar) / Pod red. M. I. Skolnika. Kniga 1. M.: Tekhno-sfera, 2015. 672 p.
D.I.Popov, The Ryazan State Radio Engineering University (RSREU), Russia, Ryazan, e-mail: adop@mail.ru Keywords:
The general principles of ARF construction for both constant and variable repetition periods are outlined. The fundamental differences in the synthesis of ARF during the wobbling of the repetition period and the associated features of the structural schemes of filters are highlighted. The considered ARFs with complex weight coefficients and ARFs with auto-compensation are classified as ARFs with full adaptation and partial adaptation when performing each of these ARFs in a canonical or cascading form. For the above variants of ARF construction, the principles of their implementation are considered, taking into account the properties of the correlation matrix of passive interference when the repetition period is wobbled. The features of ARF synthesis during the repetition period wobble are described, including the estimation of the interperiod phase shift of the clutter in each period, the asymmetry of the weight coefficients, and the estimation of the corresponding number of modules of the interperiod correlation coefficients of the clutter. Enlarged block diagrams of ARF with complex weight coefficients and with an auto-compensator are presented. The problem of optimization of non-recursive rejection filters (RF) of high orders by the probabilistic criterion is considered. The statement of the optimization problem is formulated and an expression is given for the average probability in the Doppler interval.
2. Richards M.A., Scheer J.A., Holm W.A. (Eds.). Principles of Modern Radar: Basic Principles. New York: SciTech Publishing, IET, Edison. 2010. – 924 p. 3. Melvin W. L., Scheer J.A. (Eds.). Principles of Modern Radar: Advanced Techniques. New York: SciTech Publishing, IET, Edison, 2013. – 846 p. 4. Radar Handbook / Ed. by M.I. Skolnik. 3rd ed. McGraw–Hill, 2008. 1352 p. 5. Popov D.I. Adaptive notch filter with complex weight // Vestnik Kontserna PVO «Almaz – Antej». 2015. no 2 (14). pp. 21-26. (in Russian). 6. Popov D.I. Autocompensation of the Doppler phase of clutter // Cifrovaja obrabotka signalov. 2009. no 2. pp. 30–33. (in Russian). 7. Popov D.I. Adaptive suppression of clutter // Cifrovaja obrabotka signalov. 2014. no. 4. pp. 32-37. (in Russian). 8. Popov D.I. Adaptivnije regektornjie filtrij kaskadnogo tipa // Cifrovaya obrabotka signalov. 2016. no. 2. pp. 53-56. (in Russian). 9. Popov D.I. Adaptive notch filter with real weights // Cifrovaya obrabotka signalov. 2017. no. 1. pp. 22-26. (in Russian). 10. Popov D.I. Optimizacja nerekursivnjih regektornjie filtrov s chastichnoj adaptaciej // Cifrovaya obrabotka signalov. 2018. no. 1. pp. 28-32. (in Russian). 11. Popov D.I. Rezhektirovanie passivnyh pomeh pri vobuljacii perioda povtorenija // Radiotehnika. 2015. no. 5. P. 97-101. (in Russian). 12. Popov D.I. Ocenivanie korreljacionnyh parametrov passivnyh pomeh // Radio-promyshlennost'. 2017. no. 1. P. 57-62. (in Russian). 13. Patent na izobretenie no. 2579998 RF, MPK H03H 7/12. Adaptivnyj rezhektornyj fil'tr / D.I. Popov, opubl. 10.04.2016, Bjul. no. 10. – 12 p. (in Russian). 14. Patent na izobretenie no. 2599621 RF, MPK H04B 1/10. Adaptivnyj rezhektor passivnyh pomeh / D.I. Popov, opubl. 10.10.2016, Bjul. no. 28. 16 p. (in Russian).
Based on the qualitative determination of robustness in relation to the MTI problem and the introduced criterion for the synthesis of robust algorithms, the synthesis and analysis of adaptive robust algorithms for clutter rejection are carried out. The problem of synthesis of adaptive algorithms for clutter rejection resistant to measurement errors is solved for all possible values of the es-timated parameters for the cases of equidistant and non-equidistant receipt of processed clutter samples. The synthesis and analysis of adaptive robust algorithms for clutter rejection, the main properties and advantages of which are analyticity and comparative simplicity, is carried out; as well as the possibility of achieving the maximum or close to it efficiency in the absence of measurement errors of unknown parameters of the correlation matrix of the clutter, while the maximum loss value due to not taking into ac-count the shape of the energy spectrum of the clutter, in comparison with the ex-act optimal algorithms is only a fraction of dB (in particular, for the second-order notch filter (RF) is 0.16 dB). It is shown that the existence, continuity, and modulo-boundedness of the derivatives of the vector of weight coefficients reduces the influence of a methodological or systematic measurement error. The synthesized robust algorithms for clutter detection neutralize the influence of random errors caused by various objective destabilizing factors on the calculation of the RF weight vector.
2. Richards M.A., Scheer J.A., Holm W.A. (Eds.). Principles of Modern Radar: Basic Principles. New York: SciTech Publishing, IET, Edison. 2010. – 924 p. 3. Melvin W. L., Scheer J.A. (Eds.). Principles of Modern Radar: Advanced Techniques. New York: SciTech Publishing, IET, Edison, 2013. – 846 p. 4. Radar Handbook / Ed. by M.I. Skolnik. 3rd ed. McGraw–Hill, 2008. 1352 p. 5. Popov D.I. Adaptacija nerekursivnyh rezhektornyh fil'trov // Izvestija vuzov. Ra-diojelektronika. 2009. vol. 52. no. 4. P. 46-55. (in Russian). 6. Popov D.I. Autocompensation of the Doppler phase of clutter // Cifrovaja obrabotka signalov. 2009. no 2. pp. 30–33. (in Russian). 7. Popov D.I. Adaptive suppression of clutter // Cifrovaja obrabotka signalov. 2014. no. 4. pp. 32-37. (in Russian). 8. Popov D.I. Adaptivnije regektornjie filtrij kaskadnogo tipa // Cifrovaya obrabotka signalov. 2016. no. 2. pp. 53-56. (in Russian). 9. Popov D.I. Adaptive notch filter with real weights // Cifrovaya obrabotka signalov. 2017. no. 1. pp. 22-26. (in Russian). 10. Popov D.I. Optimizacja nerekursivnjih regektornjie filtrov s chastichnoj adaptaciej // Cifrovaya obrabotka signalov. 2018. no. 1. pp. 28-32. (in Russian). 11. Popov D.I. Optimizacija rezhektornyh fil'trov po verojatnostnomu kriteriju // Cifrovaja obrabotka signalov. 2021. no. 1. P. 55-58. (in Russian). 12. Popov D.I. Rezhektirovanie passivnyh pomeh pri vobuljacii perioda povtorenija // Radiotehnika. 2015. no. 5. P. 97-101. (in Russian). 13. Popov D.I. Ustojchivost' adaptivnyh algoritmov rezhektirovanija passivnyh po-meh // Radiopromyshlennost'. 2018. no. 1. P. 87-93. (in Russian). 14. Hjuber Dzh.P. Robastnost' v statistike (Robustness in statistics). Moscow: Mir, 1984. 304 p. (in Russian). 15. Kassam S.A., Pur G.V. Robastnye metody obrabotki signalov: obzor // TIIJeR. 1985. vol. 73. no. 3. p. 54-110. (in Russian). 16. Korn G., Korn T. Spravochnik po matematike (dlja nauchnyh rabotnikov i inzhene-rov) [Handbook of Mathematics (for researchers and engineers)]. Moscow: Nauka, 1973. 832 p. (in Russian).
When the signal passes through the structure of the interpolated filter, additional spectral components appear. To exclude additional spectral components, a low-order smoothing filter is used. Therefore, the use of an interpolated filter assumes the construction of a two-stage system, including an interpolated IIR adaptive filter and an FIR or IIR smoothing filter. Experimental studies were carried using the NumPy library. The research was carried out using the RLS algorithm for both basic and two-stage adaptive filter structures. It has been shown that, when using the same adaptation algorithm, interpolated IIR filter has an advantage in both speed and convergence accuracy. The price for the improvement is the increase of the data memory in the delay line for storing intermediate samples of the signals, as well as the need to implement a smoothing filter. 2. Colin F. N., Grant P. M., Adaptive Filters. Prentice-Hall, 1985. 3. Vityazev V.V. Mnogoskorostnaya obrabotka signalov (Multirate signal processing). M.: Gorjachaja linija–Telekom, 2017. – 336 p 4. Vityazev V.V., Goriushkin R.S. Analiz ustojchivosti cifrovyh uzkopolosnyh BIH-fil'trov, realizovannyh po dvuhkaskadnoj strukture (Analysis of the stability of digital IIR narrowband filters implemented in a two-stage structure) // Cifrovaya obrabotka signalov i eyo primenenie DSPA-2018, M., 2018. Vol.1. pp. 184-189 5. Diniz P. Adaptive Filtering: Algorithms and Practical Implementation. Springer, 2020. 495 pp. 6. S. Koshita, Y. Kumamoto, M. Abe, M. Kawamata, Adaptive IIR Band-Pass/Band-Stop Filtering Using High-Order Transfer Function and Frequency Transformation, Interdisciplinary Information Sciences, 2013, Vol. 19, Issue 2, 2013, pp. 163-172 7. R. V. Raja Kumar and R. N. Pal, "Tracking of bandpass signals using center-frequency adaptive filters," in IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 38, no. 10, pp. 1710-1721, Oct. 1990 8. S. Koshita, Y. Kumamoto, M. Abe, M. Kawamata, High-order center-frequency adaptive filters using block-diagram-based frequency transformation, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, pp. 4284-4287 9. Constantinides A., Spectral Transformations for Digital Filters. Proceedings of the Institution of Electrical Engineers, pp. 1585-1590, 1970
At the control level of the logical channel, there is no provision for correcting errors that occur during transmission, but only checking their absence in the received frame by the checksum, so any distortion of the bits of the received frame will entail its retransmission in the future. At the same time, the longer the frame length in bits (bytes), the higher the probability of its distortion during transmission over the communication channel with interference. The transmitted information frame of any duration contains a mandatory service part of a fixed size. Therefore, the smaller the information part of the transmitted frame, the more of these frames will need to be transmitted to deliver the entire message and more service information of the frame headers will be transmitted along with the useful message. Consequently, an increase in the size of the transmitted information frames of the message on the one hand reduces the total time of its transmission by reducing the share of the transmitted service information of the headers, and on the other hand increases the probability of incorrect delivery of these frames, and the number of their repeated transmissions. This increases the total time to deliver the message. Therefore, an urgent task is to choose the optimal value of the volume of the information part of the message packets, which ensures the minimum average time of its delivery over the communication channel. To determine the optimal value of the volume of the information part of the message packets, a mathematical model of this process is developed and studied on the basis of the apparatus of homogeneous absorbing finite Markov chains (PCMC). Moreover, channels with different logical forward and reverse channels are considered. The first of the above mathematical models takes into account the worst quality in terms of the probability of a bit error of a direct logical data transmission channel. The second of the models under consideration allows us to determine the timeliness of delivering messages over a connected virtual connection with handshaking at the transport layer of the OSI model. 2. Protocols information and computer networks: a Handbook / S. A. Anichkin A. S. Belov, A. V. Bernstein, and others; ed. by I. Mizin, A. P. Kuleshov. – M.: Radio and communication, 1990. – 504 p.: Il. ISBN 5-256-00359-3. 3. Kazakov V. A. introduction to the theory of Markov processes and some electronic prob-lem .- M.: Sov. radio, 1973. – 232 p. 4. Potapov, S. E. Automated synthesis of finite absorbing Markov chain that describes the bringing of multi-packet messages in connection "point to point" transmission systems and the study of its efficiency [Text] / S. E. Potapov, V. A. Tsymbal, V. E. Toskin, V. V. Chapter, O. I. Sorokin, M. A. Lygin, A. A. Berezhnoy, N. In. Hooks // Radio engineering and telecommunication systems : nauch.–tekhn. jour. – Murom, 2016. – Vol. 4. (24). – P. 59-65. – ISSN 2221-2574. 5. Goldstein, A. B., Goldstein, B. S., MPLS technology and protocols. - St. Petersburg: BHV-St. Petersburg, 2005. - 304 p.: ill. 6. Olwein, V. Structure and implementation of modern MPLS technology.: Translated from English-Moscow: Williams Publishing House, 2004. - 480 p.: ill. 7. Tanenbaum E., Weatherall D. Computer networks. 5th ed. - St. Petersburg: Peter, 2012 – - 960 p.: ill. 8. Tsymbal V. A., Kosareva L. N., Isaeva T. A., Potapov S. E., Vaganov I. N. Mathematical model of multi-packet message delivery in a point-to-point connection on a data transmission net-work with the "sliding window"procedure//Proceedings of the Institute of Engineering Physics, 2009. No. 3 (13). pp. 13-19. 9. Lokhmotko V. V., Pirogov K. I. Analysis and optimization of digital integrated service networks. Mn.: Science and Technology. 2001. 192 p. 10. Parker G., Rardin R. Discrete Optimization, Academic Press, Orlando, FL, 1988. 11. Taha H. Integer Programming: Theory, Applications, and Computations, Academic Press, Orlando, FL, 1975. 12. Potapov, S. E. Relational-operator method of mathematical modeling of the transmission of multi-packet messages along virtual routes of the radio communication network // High-tech technologies in space research of the Earth. 2019. Vol. 11. No. 6. pp. 61 -73. doi: 10.24411 /2409-5419-2018-10296.
For research, we have collected our own database of colonoscopy images. The work was carried out jointly with endoscopist doctors of the Yaroslavl Regional Clinical Oncological Hospital. Today this base is closer to a real practice situation. Videos and images were taken from the Olympus CF-Q180AL and Olympus CF-Q190AL video colonoscope models, which were used with the Olympus EVIS EXERA II and EXERA III video system centers. In the course of the work, 67 video fragments of colonoscopy of 64 patients were received and processed. The average length of one video clip was 15 minutes. 6430 images of polyps with a resolution of 626x532 pixels were obtained from video fragments. A modified version of input data augmentation is proposed. When using it, the image is converted from the RGB color space to HSV, the brightness, contrast, saturation, and hue are randomized within the specified limits, the image is also randomly rotated by 90, 180, and 270 degrees with a probability of 0.5, horizontal and vertical mirroring, cut out patches from the image at random and resize them with different aspect ratios. The best results of the SSD neural network were obtained using the developed modified version of augmentation. The developed neural network algorithm has a performance sufficient for analyzing the video stream in real-time and also has relatively high values of the algorithm quality assessment metrics. The highest metric value F1 = 81.53 was obtained for the SSD algorithm with a VGG-512 backbone network. For assessing the performance of the trained neural network models, a test was carried out on a personal computer with the following characteristics: CPU AMD Ryzen 7 3800X, RAM 64 GB, GPU GeForce GTX 1080 Ti. The test measured the processing time of a short video fragment, consisting of 1249 frames. For the algorithm based on SSD VGG-300, the processing speed was 62 frames per second, for SSD VGG-512 - 55 frames per second, and for SSD MobileNet-300 - 84 frames per second. Thus, the proposed algorithms can be used to process an endoscopic video stream in real-time. A promising direction for further research is improving the quality of the proposed algorithm by post-processing the results using additional information from adjacent frames of the video stream, as well as improving the quality of the input image through the use of deinterlacing algorithms. The reported study was funded by RFBR, project number 19-37-90153. 2. Kirsanova A.V. Current state and prospects for the development of expert medical systems // New University. Series «Technical Sciences», 2015, no. 11-12, pp. 45-46. 3. Kuvaev R.O., Nikonov E.L., Kashin S.V., Kapranov V.A., Gvozdev A.A. Quality control of endoscopic studies, prospects for automated analysis of endoscopic images // Kremlin Medicine. Clinical Bulletin, 2013. no. 2, pp. 51-56. 4. Khryashchev V., Stepanova O., Lebedev A., Kashin S., Kuvaev R. Deep Learning for Gastric Pathology Detection in Endoscopic Images // // ACM International Conference Proceeding Series, 3rd International Conference on Graphics and Signal Processing, ICGSP 2019. Hong Kong, 2019. P. 90-94. 5. Khryashchev V.V., Ganin A.N., Lebedev A.A., Stepanova O.A., Kashin S.V., Kuvaev R.O. Development and analysis of an algorithm for detecting pathologies on endoscopic images of the stomach based on a convolutional neural network. Digital Signal Processing, 2018. no. 3, pp. 70-75. 6. Levin B, Lieberman D, McFarland B, Andrews K, Brooks D, Bond J et al. Screening and Surveillance for the Early Detection of Colorectal Cancer and Adenomatous Polyps, 2008: A Joint Guideline From the American Cancer Society, the US MultiSociety Task Force on Colorectal Cancer, and the American College of Radiology. Gastroenterology. 2008; 134(5). P. 1570-1595. 7. Sun X., Zhang P., Wang D., Cao Y., Liu B. Colorectal Polyp Segmentation by U-Net with Dilation Convolution. 18th IEEE International Conference On Machine Learning And Applications (ICMLA), 2019. 8. Sornapudi S., Meng F., and Yi S. Region-based automated localization of colonoscopy and wireless capsule endoscopy polyps. Applied Sciences, vol. 9, no. 12, 2019. 9. Nikolenko S.I., Kadurin A.A., Arkhangelskaya E.O. Deep Learning - SPb.: Peter, 2018. 480 p. 10. Goodfellow I., Bengio Y., Courville A. Deep learning. DMK-Press, 2017. 652 p. 11. Lebedev A.A., Khryashchev V.V., Kazina E.M., Srednyakova A.S., Zhuravleva A.S. Recognition of the orifice of the appendix on endoscopic images of the rectum based on convolutional neural network // Digital signal processing and its application (DSPA-2020): Proc. 22nd Int. conf. Moscow, 2020. pp. 638-642. 12. Khryashchev V.V., Srednyakova A.S., Ganin A.N., Kashin S.V. Using deep neural networks to search for pathologies on endoscopic images of the stomach // Digital signal processing and its application (DSPA-2021): Proc. 23rd Int. conf. Moscow, 2021. pp. 254-258. 13. Liu W., Anguelov D., Erhan D., Szegedy C., and Reed S.E. SSD: Single Shot Multibox Detector. CoRR, abs/1512.02325, 2015. 14. Bernal, J., Sanchez, F. J., Fernandez-Esparrach, G., Gil, D., Rodriguez, C., & Vilarino, F. (2015). WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians. Computerized Medical Imaging and Graphics, 43. P. 99 111. 15. Bernal, J., Sanchez, J. and Vilariño, F. ‘Towards automatic polyp detection with a polyp appearance model. Pattern Recognition. Volume 45, Issue 9, September 2012, P. 3166–3182. 16. Juan S. Silva, Aymeric Histace, Olivier Romain, Xavier Dray, Bertrand Granado, Towards embedded detection of polyps in WCE images for early diagnosis of colorectal cancer. International Journal of Computer Assisted Radiology and Surgery, Springer Verlag (Germany), 2014, 9 (2), P. 283-293. 17. Howard, A.G. Some improvements on deep convolutional neural network based image classification // arXiv preprint arXiv:1312.5402, 2013. 18. Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. In: Proceedings of ICML, 2015. P. 448-456. |