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Relevant bibliographies by topics / Optical data processing / Journal articles

Journal articles on the topic 'Optical data processing'

To see the other types of publications on this topic, follow the link: Optical data processing.

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Teller, J., F. Ozguner, and R. Ewing. "Data processing through optical interfaces." IEEE Aerospace and Electronic Systems Magazine 24, no. 10 (October 2009): 42–43. http://dx.doi.org/10.1109/maes.2009.5317786.

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2

Vâle, G., and A. Krûminsh. "Active Media for Optical Data Processing." Materials Science Forum 384-385 (January 2002): 329–32. http://dx.doi.org/10.4028/www.scientific.net/msf.384-385.329.

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3

Wu, Yarning, Liren Liu, and Zhijiang Wang. "Optical programmable shifting for data processing." Applied Optics 32, no. 26 (September 10, 1993): 4989. http://dx.doi.org/10.1364/ao.32.004989.

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4

Brenner, Karl-Heinz, and Adolf W. Lohmann. "Cyclic shifting for optical data processing." Applied Optics 27, no. 3 (February 1, 1988): 434. http://dx.doi.org/10.1364/ao.27.000434.

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5

Mehta, P. C. "Recent trends in optical data processing." Hyperfine Interactions 37, no. 1-4 (December 1987): 325–45. http://dx.doi.org/10.1007/bf02395719.

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6

NAGAE, Sadahiko. "Pattern Recognition by Optical Data Processing (3)." Journal of Graphic Science of Japan 20, no. 2 (1986): 7–13. http://dx.doi.org/10.5989/jsgs.20.2_7.

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7

MOTOYA, Yoshinobu. "Data Processing Employing an Optical Disk System." Zisin (Journal of the Seismological Society of Japan. 2nd ser.) 41, no. 3 (1988): 411–17. http://dx.doi.org/10.4294/zisin1948.41.3_411.

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8

Fateev, V. F., and A. P. Aleshkin. "Processing of multiple-site optical measurement data." Journal of Optical Technology 67, no. 7 (July 1, 2000): 634. http://dx.doi.org/10.1364/jot.67.000634.

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9

Kohler, D., M. Staehelin, and I. Zschokke-graenacher. "Organic Molecular Crystals for Optical Data Processing." Molecular Crystals and Liquid Crystals Science and Technology. Section A. Molecular Crystals and Liquid Crystals 229, no. 1 (May 1993): 117–22. http://dx.doi.org/10.1080/10587259308032184.

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10

Bräuchle, Ch, and N. Hampp. "The biopolymer bacteriorhodopsin in optical data processing." Makromolekulare Chemie. Macromolecular Symposia 50, no. 1 (October 1991): 97–105. http://dx.doi.org/10.1002/masy.19910500111.

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11

Yegorov, A. D., V. A. Yegorov, S. A. Yegorov, and I. Ye Synelnikov. "IMPROVED METHODS OF DATA PROCESSING IN OPTICAL SPECTROMETERS." Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences 3, no. 1 (2019): 46–50. http://dx.doi.org/10.32838/2663-5941/2019.3-1/08.

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12

Yunlong, Zhang, Wang Zhibin, Zhang Feng, Guo Xiaogang, and Li Junqi. "Detection and data processing of diffractive optical element." Journal of Applied Optics 39, no. 3 (2018): 52–57. http://dx.doi.org/10.5768/jao201839.0302002.

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13

SUMARU, Kimio. "Optical Parallel Data Processing Using Organic Photochromic Materials." Kobunshi 50, no. 7 (2001): 460. http://dx.doi.org/10.1295/kobunshi.50.460.

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14

Polese, D., E. Martinelli, G. Magna, F. Dini, A. Catini, R. Paolesse, I. Lundstrom, and C. Di Natale. "Sharing data processing among replicated optical sensor arrays." Sensors and Actuators B: Chemical 179 (March 2013): 252–58. http://dx.doi.org/10.1016/j.snb.2012.10.032.

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15

Guest, Clark C., and Thomas K. Gaylord. "Phase stabilization system for holographic optical data processing." Applied Optics 24, no. 14 (July 15, 1985): 2140. http://dx.doi.org/10.1364/ao.24.002140.

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16

Collet, J. H., and M. Pugnet. "Picosecond Plasma Dynamics and All-Optical Data Processing." physica status solidi (b) 146, no. 1 (March 1, 1988): 393–401. http://dx.doi.org/10.1002/pssb.2221460142.

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17

Turitsyn, Sergei K., Jaroslaw E. Prilepsky, Son Thai Le, Sander Wahls, Leonid L. Frumin, Morteza Kamalian, and Stanislav A. Derevyanko. "Nonlinear Fourier transform for optical data processing and transmission: advances and perspectives." Optica 4, no. 3 (February 28, 2017): 307. http://dx.doi.org/10.1364/optica.4.000307.

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18

Likhachev, Aleksey V., and Marina V. Tabanyukhova. "A new processing algorithm for photoelasticity method data." Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mekhanika, no. 79 (2022): 100–110. http://dx.doi.org/10.17223/19988621/79/9.

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The photoelasticity method is a reliable tool for studying the stress state of flat elements in building structures using the models made of optically sensitive materials. In this paper, the classical photoelasticity is considered. The experimental data obtained with the use of the method are presented as interferograms. A decoding procedure implies the obtaining of some normal and tangential stress values in the plane of the model. The polarization-projection installations that are used in optical methods are rather simple. However, the digital processing of the images obtained during the loaded model transmission requires high-intelligent software. Nowadays, national and international laboratories, working with polarization-optical methods, strive to develop digital photoelasticity. For some reasons, the authors of the presented work needed to develop their own algorithms for decoding experimental data of the photoelasticity method. This work is mainly devoted to a formulation of the problems to be solved. Some of them have already been solved, and the results obtained are presented here. The authors place special emphasis on the description of the algorithm for tracing of interference fringes based on the analysis of the image gradient.

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19

Wang, Jian. "Chip-scale optical interconnects and optical data processing using silicon photonic devices." Photonic Network Communications 31, no. 2 (July 23, 2015): 353–72. http://dx.doi.org/10.1007/s11107-015-0525-z.

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20

Tan Zhongwei, 谭中伟, 秦凤杰 Qin Fengjie, 任文华 Ren Wenhua, and 刘艳 Liu Yan. "Application of Fiber Dispersion in All Optical Data Processing." Laser & Optoelectronics Progress 50, no. 8 (2013): 080023. http://dx.doi.org/10.3788/lop50.080023.

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21

Wohlfeil, J., A. Börner, M. Buder, I. Ernst, D. Krutz, and R. Reulke. "REAL TIME DATA PROCESSING FOR OPTICAL REMOTE SENSING PAYLOADS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B5 (July 24, 2012): 63–68. http://dx.doi.org/10.5194/isprsarchives-xxxix-b5-63-2012.

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22

Tanida, Jun, and Yoshiki Ichioka. "Programming of optical array logic 1: Image data processing." Applied Optics 27, no. 14 (July 15, 1988): 2926. http://dx.doi.org/10.1364/ao.27.002926.

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23

Ewen, J. F., K. P. Jackson, R. J. S. Bates, and E. B. Flint. "GaAs fiber-optic modules for optical data processing networks." Journal of Lightwave Technology 9, no. 12 (1991): 1755–63. http://dx.doi.org/10.1109/50.108721.

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24

Pilipovich, V. A., A. K. Esman, I. A. Goncharenko, and V. K. Kuleshov. "Optical data switching in information processing and measuring systems." Measurement Techniques 47, no. 9 (September 2004): 879–83. http://dx.doi.org/10.1007/s11018-005-0034-z.

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25

Touch, Joe, Yinwen Cao, Morteza Ziyadi, Ahmed Almaiman, Amirhossein Mohajerin-Ariaei, and Alan E. Willner. "Digital optical processing of optical communications: towards an Optical Turing Machine." Nanophotonics 6, no. 3 (January 24, 2017): 507–30. http://dx.doi.org/10.1515/nanoph-2016-0145.

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AbstractOptical computing is needed to support Tb/s in-network processing in a way that unifies communication and computation using a single data representation that supports in-transit network packet processing, security, and big data filtering. Support for optical computation of this sort requires leveraging the native properties of optical wave mixing to enable computation and switching for programmability. As a consequence, data must be encoded digitally as phase (M-PSK), semantics-preserving regeneration is the key to high-order computation, and data processing at Tb/s rates requires mixing. Experiments have demonstrated viable approaches to phase squeezing and power restoration. This work led our team to develop the first serial, optical Internet hop-count decrement, and to design and simulate optical circuits for calculating the Internet checksum and multiplexing Internet packets. The current exploration focuses on limited-lookback computational models to reduce the need for permanent storage and hybrid nanophotonic circuits that combine phase-aligned comb sources, non-linear mixing, and switching on the same substrate to avoid the macroscopic effects that hamper benchtop prototypes.

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26

Lv, Shuo. "All-Optical Signal Processing in Ultrafast Optical Communication." Highlights in Science, Engineering and Technology 53 (June 30, 2023): 108–15. http://dx.doi.org/10.54097/hset.v53i.9689.

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Optical communication technology plays a crucial role in today's information age, as a result of the continuous advancement of social informatization. An array of nascent technologies, encompassing edge computing, the Internet of Things, big data, and artificial intelligence, have grown rapidly, leading to an increased demand for information transmission, which in turn has resulted in higher requirements for the development of optical communication technology. The emergence of ultrafast optical communication, which uses all-optical signal processing technology, has made data transmission faster and more reliable. This article introduces three basic methods for implementing all-optical signal processing (optical modulation, regeneration, and interconnection) based on all-optical and electronic signal processing. It examines the issues and difficulties that arise within particular application contexts and explores the progression of several correlated technologies in the times ahead. The field of all-optical signal processing is experiencing rapid growth and has the potential to bring revolutionary changes to various industries. Anticipated outcomes entail the attainment of ultra-long distance and ultra-high-capacity transmission, as facilitated by the ongoing advancements in hardware and all-optical signal processing technology. Meanwhile, the relentless pursuit of high-performance goals drives the continuous progress of ultrafast optical communication.

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27

SHENG Lei, 盛磊, 吴志勇 WU Zhi-yong, 刘旨春 LIU Zhi-chun, 高策 Gao Ce, 张世学 ZHANG Shi-xue, and 王世刚 WANG Shi-gang. "Data processing for shipboard theodolite." Optics and Precision Engineering 21, no. 9 (2013): 2421–29. http://dx.doi.org/10.3788/ope.20132109.2421.

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28

Li, Shuang, Shanchuan Liao, Wenjing Li, Luqun Li, and Dazhi Li. "Research on Key Technologies of Data Processing Mechanisms in Ternary Optical Computer." Applied Sciences 14, no. 13 (June 27, 2024): 5598. http://dx.doi.org/10.3390/app14135598.

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This paper introduces an arithmetic data file, a key technology for data processing in a ternary optical computer (TOC). The physical form of the ternary optical processor and its data processing characteristics are analyzed. Based on this analysis, the compution-data is constructed, and research is carried out on the format of the compution-data, its generation method, and the expansion of high-level languages transmitted to the ternary optical processor. The calculation rules and the raw data for the ternary optical computer are organized into a file that conforms to the calculation characteristics of the computer. A data processing mechanism based on the compution-data is proposed. Finally, an experimental test was conducted on the platform of a ternary optical computer using specific examples. The results showed that by organizing and transmitting data through the compution-data, the ternary optical computer could fully utilize its computational advantages in data processing while shielding the underlying complex hardware processing. This makes it convenient for users to apply this new type of computer. This data processing mechanism can offer a novel perspective for other heterogeneous systems in data processing.

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29

Wnęk, Karol, and Piotr Boryło. "A Data Processing and Distribution System Based on Apache Nifi." Photonics 10, no. 2 (February 15, 2023): 210. http://dx.doi.org/10.3390/photonics10020210.

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The monitoring of physical and logical networks is essential for the high availability of 5G/6G networks. This could become a challenge in 5G/6G deployments due to the heterogeneity of the optical layer. It uses equipment from multiple vendors, and, as a result, the protocols and methods for gathering monitoring data usually differ. Simultaneously, to effectively support 5G/6G networks, the optical infrastructure should also be dense and ensure high throughput. Thus, vast numbers of photonic transceivers operating at up to 400 Gbps are needed to interconnect network components. In demanding optical solutions for 5G and beyond, enterprise-class equipment will be used—for example, high-capacity and high-density optical switches based on the SONiC distribution. These emerging devices produce vast amounts of data on the operational parameters of each optical transceiver, which should be effectively collected, processed, and analyzed. The aforementioned circumstances may lead to the necessity of using multiple independent monitoring systems dedicated to specific optical hardware. Apache NiFi can be used to address these potential issues. Its high configurability enables the aggregation of unstandardized log files collected from heterogenous devices. Furthermore, it is possible to configure Apache NiFi to absorb huge data streams about each of the thousands of transceivers comprising high-density optical switches. In this way, data can be preprocessed by using Apache NiFi and later uploaded to a dedicated system. In this paper, we focus on presenting the tool, its capabilities, and how it scales horizontally. The proven scalability is essential for making it usable in optical networks that support 5G/6G networks. Finally, we propose a unique optimization process that can greatly improve the performance and make Apache NiFi suitable for high-throughput and high-density photonic devices and optical networks. We also present some insider information on real-life implementations of Apache NiFi in commercial 5G networks that fully rely on optical networks.

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30

GAYEN, DILIP KUMAR, CHINMOY TARAPHDAR, JITENDRA NATH ROY, and RAJAT KUMAR PAL. "TERAHERTZ OPTICAL ASYMMETRIC DEMULTIPLEXER BASED ALL OPTICAL DATA COMPARATOR." Journal of Circuits, Systems and Computers 19, no. 03 (May 2010): 671–82. http://dx.doi.org/10.1142/s0218126610006359.

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An all-optical data comparator with the help of Terahertz Optical Asymmetric Demultiplexer (TOAD) is proposed. The paper describes the all-optical data comparator by using a set of all-optical full-adder and optical switch. Comparison between two binary data is required in many data processing systems. It is sometimes necessary to know whether a binary number is greater than, equal to, or less than another number. The all-optical data comparator can be used to perform a fast central processor unit using optical hardware components. In this present communication, we have tried to exploit the advantages of TOAD-based switch to design an integrated all-optical circuit which can perform data comparison operations.

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31

Oxenløwe, L. K., M. Galili, H. C. Hansen Mulvad, H. Hu, J. L. Areal, E. Palushani, H. Ji, A. T. Clausen, and P. Jeppesen. "Nonlinear Optical Signal Processing for Tbit/s Ethernet Applications." International Journal of Optics 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/573843.

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Wereviewrecent experimental demonstrations of Tbaud optical signal processing. In particular, we describe a successful 1.28 Tbit/s serial data generation based on single polarization 1.28 Tbaud symbol rate pulses with binary data modulation (OOK) and subsequent all-optical demultiplexing. We also describe the first error-free 5.1 Tbit/s data generation and demodulation based on a single laser, where a 1.28 Tbaud symbol rate is used together with quaternary phase modulation (DQPSK) and polarization multiplexing. The 5.1 Tbit/s data signal is all-optically demultiplexed and demodulated by direct detection in a delay-interferometer-balanced detector-based receiver, yielding a BER less than 10−9. We also present subsystems making serial optical Tbit/s systems compatible with standard Ethernet data for data centre applications and present Tbit/s results using, for instance silicon nanowires.

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32

Rashed, Ahmed Nabih Zaki, and Mohammed Salah F. Tabbour. "Suitable Optical Fiber Communication Channel for Optical Nonlinearity Signal Processing in High Optical Data Rate Systems." Wireless Personal Communications 97, no. 1 (May 24, 2017): 397–416. http://dx.doi.org/10.1007/s11277-017-4511-x.

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33

Tan Zhongqi, 谭中奇, 吴素勇 Wu Suyong, 刘贱平 Liu Jianping, 杨开勇 Yang Kaiyong, and 龙兴武 Long Xingwu. "Spectrum data processing in optical-feedback cavity ring-down spectroscopy." High Power Laser and Particle Beams 26, no. 10 (2014): 101006. http://dx.doi.org/10.3788/hplpb20142610.101006.

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34

Grigor'ev, A. N., A. I. Altuchov, and D. S. Korshunov. "An approach to photogrammetric processing of indirect optical location data." Scientific and Technical Journal of Information Technologies, Mechanics and Optics 21, no. 3 (June 1, 2021): 311–19. http://dx.doi.org/10.17586/2226-1494-2021-21-3-311-319.

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35

Kokodii, N. G., V. О. Timaniuk, E. Ya Levitin, and M. V. Kaydash. "ATTENUATION OF OPTICAL RADIATION BY NANOPARTICLES: ALGORITHM FOR DATA PROCESSING." Telecommunications and Radio Engineering 76, no. 10 (2017): 919–27. http://dx.doi.org/10.1615/telecomradeng.v76.i10.80.

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36

Wherrett, B. S., and S. D. Smith. "Bistable Semiconductor Elements for Optical Data Processing and Photonic Logic." Physica Scripta T13 (January 1, 1986): 189–94. http://dx.doi.org/10.1088/0031-8949/1986/t13/032.

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37

Watson, J., and G. Mackay. "Inspection of Integrated Circuit Photomasks using Optical Data Processing Techniques." Journal of Photographic Science 34, no. 1 (January 1986): 1–10. http://dx.doi.org/10.1080/00223638.1986.11738384.

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38

Nakamura, M., B. Leskovar, and B. Turko. "Signal processing for an optical wide band data transmission system." IEEE Transactions on Nuclear Science 35, no. 1 (1988): 197–204. http://dx.doi.org/10.1109/23.12706.

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39

Greated, Clive. "Optical methods and data processing in heat and fluid flow." Optics & Laser Technology 24, no. 5 (October 1992): 308. http://dx.doi.org/10.1016/0030-3992(92)90080-l.

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40

Zhang, Qiang, Xiaoying Liang, and Xiaopeng Wei. "Scattered Data Processing Approach Based on Optical Facial Motion Capture." Applied Bionics and Biomechanics 10, no. 2-3 (2013): 75–87. http://dx.doi.org/10.1155/2013/463235.

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In recent years, animation reconstruction of facial expressions has become a popular research field in computer science and motion capture-based facial expression reconstruction is now emerging in this field. Based on the facial motion data obtained using a passive optical motion capture system, we propose a scattered data processing approach, which aims to solve the common problems of missing data and noise. To recover missing data, given the nonlinear relationships among neighbors with the current missing marker, we propose an improved version of a previous method, where we use the motion of three muscles rather than one to recover the missing data. To reduce the noise, we initially apply preprocessing to eliminate impulsive noise, before our proposed three-order quasi-uniform B-spline-based fitting method is used to reduce the remaining noise. Our experiments showed that the principles that underlie this method are simple and straightforward, and it delivered acceptable precision during reconstruction.

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41

Petrov, V. V., A. A. Kryuchin, S. M. Shanoylo, and V. I. Sidorenko. "Optical Disks as a Basis of Modern Paperless Data Processing." Cybernetics and Systems Analysis 39, no. 5 (September 2003): 777–82. http://dx.doi.org/10.1023/b:casa.0000012098.70754.13.

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42

Bräuchle, C., and N. Hampp. "Optical Data Processing with Bacteriorhodopsin and its Genetically Modified Variants." Molecular Crystals and Liquid Crystals Science and Technology. Section A. Molecular Crystals and Liquid Crystals 216, no. 1 (June 1992): 43–48. http://dx.doi.org/10.1080/10587259208028747.

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43

Abushagur, Mustafa A. G. "Adaptive array radar data processing using the bimodal optical computer." Microwave and Optical Technology Letters 1, no. 7 (September 1988): 236–40. http://dx.doi.org/10.1002/mop.4650010704.

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44

Kopenkov, V. N. "Combined usage of the optical and radar remote sensing data in territory monitoring tasks." Information Technology and Nanotechnology, no. 2391 (2019): 334–41. http://dx.doi.org/10.18287/1613-0073-2019-2391-334-341.

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At the present time, a lot of problems in a sphere of fundamental sciences as well as technical and applied tasks can be solved only with the use of satellite images, since their usage reduces material, financial and time costs significantly in comparison with traditional methods. One of the modern integrated approach remote sensing processing is to join the measurements obtained from the various sources, such as optical and radar sensors, allowing to achieve a gain in comparison with independent processing due to the extension of the information volume and the opportunities of data acquisition (weather conditions, spectral ranges, etc.). However, methods of digital processing and interpretation of radar data, as well as qualitative and proven methods and algorithms for joint processing of optical and radar satellite images, has not sufficiently been well developed yet. Therefore, the development of new methods and information technology of joint analysis and interpretation of optical and radar data which are a major issue of the current paper, are certainly relevant. The paper presents an information technology for joint processing of optical and radar satellite imagery, based on training the processing procedure based on the reference values of data from sensors of the one type (optical data), followed by applying to both data types: optical and SAR data.

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45

Laughner, Jacob I., Fu Siong Ng, Matthew S. Sulkin, R. Martin Arthur, and Igor R. Efimov. "Processing and analysis of cardiac optical mapping data obtained with potentiometric dyes." American Journal of Physiology-Heart and Circulatory Physiology 303, no. 7 (October 1, 2012): H753—H765. http://dx.doi.org/10.1152/ajpheart.00404.2012.

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Optical mapping has become an increasingly important tool to study cardiac electrophysiology in the past 20 years. Multiple methods are used to process and analyze cardiac optical mapping data, and no consensus currently exists regarding the optimum methods. The specific methods chosen to process optical mapping data are important because inappropriate data processing can affect the content of the data and thus alter the conclusions of the studies. Details of the different steps in processing optical imaging data, including image segmentation, spatial filtering, temporal filtering, and baseline drift removal, are provided in this review. We also provide descriptions of the common analyses performed on data obtained from cardiac optical imaging, including activation mapping, action potential duration mapping, repolarization mapping, conduction velocity measurements, and optical action potential upstroke analysis. Optical mapping is often used to study complex arrhythmias, and we also discuss dominant frequency analysis and phase mapping techniques used for the analysis of cardiac fibrillation.

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46

Filipponi, Federico. "River Color Monitoring Using Optical Satellite Data." Proceedings 2, no. 10 (June 13, 2018): 569. http://dx.doi.org/10.3390/iecg_2018-05336.

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Knowledge of inland water quality and riverine inputs to oceans is fundamental for water management, environmental monitoring, and the definition of policies and planning strategies related to the sustainable use of rivers. While European Union directives aim at the conservation of inland water resources, the ground operational monitoring network is often inadequate. River monitoring using Remote Sensing may complement in-situ measurements, supplying continuous, spatially explicit representation of parameters related to water quality and solid transport, even if the high-frequency dynamics of water parameters may not be caught due to limited satellite revisit time. Sentinel-2 and Landsat-8 satellites, equipped with MSI and OLI optical sensors whose spectral bands perform a more accurate atmospheric correction, allow for the development of methodologies for monitoring river color from space, thanks to high spatial resolution and short revisit times. This study presents a processing chain, developed to monitor water constituents in rivers using high-resolution satellite images. Multi-temporal analysis of chlorophyll-a (Chl-a) and total suspended matter (TSM) bio-geophysical variables was performed for the case study of the Po River (Italy) for the year 2017. Quantitative estimations of water constituents were retrieved from Sentinel-2 optical multispectral satellite data using the C2RCC algorithm, and the main outcomes are discussed. The developed processing chain can be used to create operational services for river monitoring, and represent a major improvement in the identification of spatio-temporal dynamics (like solid transport) in riverine systems.

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47

Puerto-Leguizamón, Gustavo, Beatriz Ortega, José Capmany, Karen Cardona-Urrego, and Carlos Suárez-Fajardo. "Data networking evolution: Toward an all-optical n all-optical communications platform." Revista Facultad de Ingeniería Universidad de Antioquia, no. 45 (January 16, 2014): 148–56. http://dx.doi.org/10.17533/udea.redin.18121.

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An introduction to optical networks in which the evolution undergone by such networks is presented in order to manage the future demand on the transport of IP traffic is described. This evolution has been boosted by the deployment of all optical devices featuring all optical processing capabilities. Similarly, an all optical packet router is presented based on the label swapping paradigm with the ability to route and forward IP packets at 10 Gb/s. The proposed router is able to process variable length packets and its performance is experimentally verified.

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48

Mal'tsev, G. N. "Organization of optical observations and processing of data concerning space junk." Journal of Optical Technology 68, no. 10 (October 1, 2001): 777. http://dx.doi.org/10.1364/jot.68.000777.

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49

Castillo, Sergio Garcia, and Krikor B. Ozanyan. "Field-programmable data acquisition and processing channel for optical tomography systems." Review of Scientific Instruments 76, no. 9 (September 2005): 095109. http://dx.doi.org/10.1063/1.2042727.

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50

Rebane, K. K., and P. M. Saari. "Spectral Hole Burning and its Applications for Picosecond Optical Data-Processing." Physica Scripta T19B (January 1, 1987): 604–11. http://dx.doi.org/10.1088/0031-8949/1987/t19b/046.

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