СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY
The paper deals with the basic principles of signals representation in optical coherence tomography with the usage of dynamic systems theory formalism. Computational complexity of algorithms for dynamic estimation of signals parameters is analyzed, such as extended Kalman filter and sequential Mon...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)
2014-11-01
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| Series: | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| Subjects: | |
| Online Access: | http://ntv.ifmo.ru/file/article/11187.pdf |
| _version_ | 1818261285523947520 |
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| author | Maxim A. Volynsky Igor P. Gurov Peter A. Ermolaev Pavel S. Skakov |
| author_facet | Maxim A. Volynsky Igor P. Gurov Peter A. Ermolaev Pavel S. Skakov |
| author_sort | Maxim A. Volynsky |
| collection | DOAJ |
| description | The paper deals with the basic principles of signals representation in optical coherence tomography with the usage
of dynamic systems theory formalism. Computational complexity of algorithms for dynamic estimation of signals parameters
is analyzed, such as extended Kalman filter and sequential Monte-Carlo method. It is shown that processing time of one
discrete-time sample of the signal by extended Kalman filter increases polynomially with sizes of parameters vector and
observation vector. Processing time of one discrete-time sample of the signal by sequential Monte-Carlo method depends
linearly both on sizes of parameters vector and observation vector, and on the number of generating random vectors.
Experimental results of processing time measurement by each algorithm are described. It is shown that processing time of the
signal containing 500 discrete-time samples by extended Kalman filter in the case of the simplest model is approximately
equal to 0.1 seconds and increases several times with complication of the model. Processing time of the same signal by
sequential Monte-Carlo methods with fixed number of generated random vectors is equal to 0.7 seconds and slightly
increases with complication of the model, approximately by 1.5 times. Obtained results may be used for estimation of
expected data processing time by recurrent dynamic estimation algorithms in optical coherence tomography systems. |
| first_indexed | 2024-12-12T18:44:48Z |
| format | Article |
| id | doaj.art-f15a6ceabd3943e886274fa4b4bbab62 |
| institution | Directory Open Access Journal |
| issn | 2226-1494 2500-0373 |
| language | English |
| last_indexed | 2024-12-12T18:44:48Z |
| publishDate | 2014-11-01 |
| publisher | Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University) |
| record_format | Article |
| series | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| spelling | doaj.art-f15a6ceabd3943e886274fa4b4bbab622022-12-22T00:15:33ZengSaint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki2226-14942500-03732014-11-011463540СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHYMaxim A. Volynsky 0Igor P. Gurov 1Peter A. Ermolaev 2Pavel S. Skakov 3PhD, Associate professor, ITMO University, Saint Petersburg, 197101, Russian FederationD.Sc., Professor, Department head, ITMO University, Saint Petersburg, 197101, Russian Federationstudent, ITMO University, Saint Petersburg, 197101, Russian Federationassistant, ITMO University, Saint Petersburg, 197101, Russian FederationThe paper deals with the basic principles of signals representation in optical coherence tomography with the usage of dynamic systems theory formalism. Computational complexity of algorithms for dynamic estimation of signals parameters is analyzed, such as extended Kalman filter and sequential Monte-Carlo method. It is shown that processing time of one discrete-time sample of the signal by extended Kalman filter increases polynomially with sizes of parameters vector and observation vector. Processing time of one discrete-time sample of the signal by sequential Monte-Carlo method depends linearly both on sizes of parameters vector and observation vector, and on the number of generating random vectors. Experimental results of processing time measurement by each algorithm are described. It is shown that processing time of the signal containing 500 discrete-time samples by extended Kalman filter in the case of the simplest model is approximately equal to 0.1 seconds and increases several times with complication of the model. Processing time of the same signal by sequential Monte-Carlo methods with fixed number of generated random vectors is equal to 0.7 seconds and slightly increases with complication of the model, approximately by 1.5 times. Obtained results may be used for estimation of expected data processing time by recurrent dynamic estimation algorithms in optical coherence tomography systems.http://ntv.ifmo.ru/file/article/11187.pdfoptical coherence tomographyinterferometric signals processingcomputational complexityextended Kalman filtersequential Monte-Carlo method |
| spellingShingle | Maxim A. Volynsky Igor P. Gurov Peter A. Ermolaev Pavel S. Skakov СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki optical coherence tomography interferometric signals processing computational complexity extended Kalman filter sequential Monte-Carlo method |
| title | СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY |
| title_full | СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY |
| title_fullStr | СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY |
| title_full_unstemmed | СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY |
| title_short | СOMPUTATIONAL COMPLEXITY ANALYSIS OF RECURRENT DATA PROCESSING ALGORITHMS IN OPTICAL COHERENCE TOMOGRAPHY |
| title_sort | сomputational complexity analysis of recurrent data processing algorithms in optical coherence tomography |
| topic | optical coherence tomography interferometric signals processing computational complexity extended Kalman filter sequential Monte-Carlo method |
| url | http://ntv.ifmo.ru/file/article/11187.pdf |
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