Thematische Bibliographien / Detection codes

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Auswahl der wissenschaftlichen Literatur zum Thema „Detection codes“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 4. Februar 2022

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Zeitschriftenartikel zum Thema "Detection codes"

Alekseev, Maksim. „On Strengthening of Weak Algebraic Manipulation Detection Codes“. International Journal of Embedded and Real-Time Communication Systems 6, Nr. 2 (April 2015): 1–26. http://dx.doi.org/10.4018/ijertcs.2015040101.

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Algebraic manipulation detection codes were introduced in 2008 to protect data against a special type of its modification – an algebraic manipulation. There are three classes of codes: weak, strong and stronger ones. Weak codes detect only weak algebraic manipulations, while strong and stronger are capable to detect both weak and strong manipulations. In this paper, a method to transform codes from weak to stronger is described resulting in a construction of generalized robust codes. The proposed construction forms the second known family of stronger AMD codes. Codes provide simple procedures of error detectiona and correction, and allow using multi-code codec design that makes it applicable in fault-tolerant computing, storage and cryptographic devices.

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Cramer, Ronald, Serge Fehr und Carles Padró. „Algebraic manipulation detection codes“. Science China Mathematics 56, Nr. 7 (Juli 2013): 1349–58. http://dx.doi.org/10.1007/s11425-013-4654-5.

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Ford, Elizabeth, John A. Carroll, Helen E. Smith, Donia Scott und Jackie A. Cassell. „Extracting information from the text of electronic medical records to improve case detection: a systematic review“. Journal of the American Medical Informatics Association 23, Nr. 5 (05.02.2016): 1007–15. http://dx.doi.org/10.1093/jamia/ocv180.

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Abstract Background Electronic medical records (EMRs) are revolutionizing health-related research. One key issue for study quality is the accurate identification of patients with the condition of interest. Information in EMRs can be entered as structured codes or unstructured free text. The majority of research studies have used only coded parts of EMRs for case-detection, which may bias findings, miss cases, and reduce study quality. This review examines whether incorporating information from text into case-detection algorithms can improve research quality. Methods A systematic search returned 9659 papers, 67 of which reported on the extraction of information from free text of EMRs with the stated purpose of detecting cases of a named clinical condition. Methods for extracting information from text and the technical accuracy of case-detection algorithms were reviewed. Results Studies mainly used US hospital-based EMRs, and extracted information from text for 41 conditions using keyword searches, rule-based algorithms, and machine learning methods. There was no clear difference in case-detection algorithm accuracy between rule-based and machine learning methods of extraction. Inclusion of information from text resulted in a significant improvement in algorithm sensitivity and area under the receiver operating characteristic in comparison to codes alone (median sensitivity 78% (codes + text) vs 62% (codes), P = .03; median area under the receiver operating characteristic 95% (codes + text) vs 88% (codes), P = .025). Conclusions Text in EMRs is accessible, especially with open source information extraction algorithms, and significantly improves case detection when combined with codes. More harmonization of reporting within EMR studies is needed, particularly standardized reporting of algorithm accuracy metrics like positive predictive value (precision) and sensitivity (recall).

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Das, P. K. „Codes on Key Errors“. Cybernetics and Information Technologies 14, Nr. 2 (15.07.2014): 31–37. http://dx.doi.org/10.2478/cait-2014-0017.

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Abstract Coding theory has started with the intention of detection and correction of errors which have occurred during communication. Different types of errors are produced by different types of communication channels and accordingly codes are developed to deal with them. In 2013 Sharma and Gaur introduced a new kind of an error which will be termed “key error”. This paper obtains the lower and upper bounds on the number of parity-check digits required for linear codes capable for detecting such errors. Illustration of such a code is provided. Codes capable of simultaneous detection and correction of such errors have also been considered.

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Chen, Chaofan, Li Li, Li Wang, Shuai Wang, Xiangming Li und George K. Karagiannidis. „Noncoherent Detection With Polar Codes“. IEEE Access 7 (2019): 6362–72. http://dx.doi.org/10.1109/access.2018.2889498.

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Klove, T. „Optimal codes for error detection“. IEEE Transactions on Information Theory 38, Nr. 2 (März 1992): 479–89. http://dx.doi.org/10.1109/18.119708.

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Condo, Carlo, Seyyed Ali Hashemi und Warren J. Gross. „Blind Detection With Polar Codes“. IEEE Communications Letters 21, Nr. 12 (Dezember 2017): 2550–53. http://dx.doi.org/10.1109/lcomm.2017.2748940.

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Guo, Ying, und Guihua Zeng. „Quantum Event-Error Detection Codes“. Journal of the Physical Society of Japan 74, Nr. 11 (15.11.2005): 2949–56. http://dx.doi.org/10.1143/jpsj.74.2949.

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Siddharth, A. „Error detection in numeric codes“. Resonance 17, Nr. 7 (Juli 2012): 653–71. http://dx.doi.org/10.1007/s12045-012-0070-3.

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Shutao, Xia, und Fu Fangwei. „Combinatorial codes for error detection“. Acta Mathematicae Applicatae Sinica 15, Nr. 4 (Oktober 1999): 444–46. http://dx.doi.org/10.1007/bf02684046.

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Dissertationen zum Thema "Detection codes"

Xu, Danfeng. „Iterative coded multiuser detection using LDPC codes“. Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27939.

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Multiuser detection (MUD) has been regarded as an effective technique for combating cochannel interference (CCI) in time-division multiple access (TDMA) systems and multiple access interference (MAI) in code-division multiple access (CDMA) systems. An optimal multiuser detector for coded multiuser systems is usually practically infeasible due to the associated complexity. An iterative receiver consisting of a soft-input soft-output (SISO) multiuser detector and a bank of SISO single user decoders can provide a system performance which approaches to that of single user system after a few iterations. In this thesis, MUD and LDPC decoding are combined to improve the multiuser receiver performance. The soft output of the LDPC decoder is fed back to the multiuser detector to improve the detection. This leads to decision variables that have a smaller MAI component. These decision variables are then returned to the decoder and the decoding process benefits from the improvement to the decision variables. The process can be repeated many times. The resulting iterative multiuser receiver is designed based on the soft parallel interference cancellation (PIC) algorithm. For the interference reconstruction, the LDPC decoder is improved to produce the log-likelihood ratios (LLR) of the information bits as well as the parity bits. A sub-optimal approach is proposed to output the LLR of the parity bits with very low complexity. Thanks to the powerful error-correction ability of the LDPC decoder, the LDPC multiuser receiver can achieve a satisfactory convergence, and substantially outperforms non-iterative receivers. Three types of SISO multiuser detectors are provided. They are: Soft Interference Cancellation (SIC) detector, SISO decorrelating detector and SISO minimum mean square error (MMSE) detector. The resulting system performance converges very quickly. The comparison of these three types of detectors is also shown in this thesis.

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Schiffel, Ute. „Hardware Error Detection Using AN-Codes“. Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-69872.

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Due to the continuously decreasing feature sizes and the increasing complexity of integrated circuits, commercial off-the-shelf (COTS) hardware is becoming less and less reliable. However, dedicated reliable hardware is expensive and usually slower than commodity hardware. Thus, economic pressure will most likely result in the usage of unreliable COTS hardware in safety-critical systems. The usage of unreliable, COTS hardware in safety-critical systems results in the need for software-implemented solutions for handling execution errors caused by this unreliable hardware. In this thesis, we provide techniques for detecting hardware errors that disturb the execution of a program. The detection provided facilitates handling of these errors, for example, by retry or graceful degradation. We realize the error detection by transforming unsafe programs that are not guaranteed to detect execution errors into safe programs that detect execution errors with a high probability. Therefore, we use arithmetic AN-, ANB-, ANBD-, and ANBDmem-codes. These codes detect errors that modify data during storage or transport and errors that disturb computations as well. Furthermore, the error detection provided is independent of the hardware used. We present the following novel encoding approaches: - Software Encoded Processing (SEP) that transforms an unsafe binary into a safe execution at runtime by applying an ANB-code, and - Compiler Encoded Processing (CEP) that applies encoding at compile time and provides different levels of safety by using different arithmetic codes. In contrast to existing encoding solutions, SEP and CEP allow to encode applications whose data and control flow is not completely predictable at compile time. For encoding, SEP and CEP use our set of encoded operations also presented in this thesis. To the best of our knowledge, we are the first ones that present the encoding of a complete RISC instruction set including boolean and bitwise logical operations, casts, unaligned loads and stores, shifts and arithmetic operations. Our evaluations show that encoding with SEP and CEP significantly reduces the amount of erroneous output caused by hardware errors. Furthermore, our evaluations show that, in contrast to replication-based approaches for detecting errors, arithmetic encoding facilitates the detection of permanent hardware errors. This increased reliability does not come for free. However, unexpectedly the runtime costs for the different arithmetic codes supported by CEP compared to redundancy increase only linearly, while the gained safety increases exponentially.

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Xiao, Jiaxi. „Information theoretic approach in detection and security codes“. Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43620.

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Signal detection plays a critical role in realizing reliable transmission through communication systems. In this dissertation, by applying information theoretic approach, efficient detection schemes and algorithms are designed for three particular communication systems. First, a computation efficient coding and detection algorithm is developed to decode two dimensional inter-symbol interference (ISI) channels. The detection algorithm significantly reduces the computation complexity and makes the proposed equalization algorithm applicable. A new metric, the post-detection mutual information (PMI), is established to quantify the ultimate information rate between the discrete inputs and the hard detected output. This is the first time that the information rate loss caused by the hard mapping of the detectors is considered. Since the hard mapping step in the detector is irreversible, we expect that the PMI is reduced compared to the MI without hard mapping. The conclusion is confirmed by both the simulation and the theoretic results. Random complex field code is designed to achieve the secrecy capacity of wiretap channel with noiseless main channel and binary erasure eavesdroppers' channel. More importantly, in addition to approaching the secrecy capacity, RCFC is the first code design which provides a platform to tradeoff secrecy performance with the erasure rate of the eavesdropper's channel and the secrecy rate.

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Gu, Yu. „Noncoherent communications using space-time trellis codes“. Thesis, University of Canterbury. Electrical and Computer Engineering, 2008. http://hdl.handle.net/10092/1252.

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In the last decade much interest has been shown in space-time trellis codes (STTCs) since they can offer coding gain along with the ability to exploit the space and time diversity of MIMO channels. STTCs can be flexibly designed by trading off performance versus complexity. The work of Dayal [1] stated that if training symbols are used together with data symbols, then a space-time code can be viewed as a noncoherent code. The authors of [1] described the migration from coherent space-time codes to training assisted noncoherent space-time codes. This work focuses on the development of training assisted noncoherent STTCs, thus extending the concept of noncoherent training codes to STTCs. We investigate the intrinsic link between coherent and noncoherent demod- ulation. By analyzing noncoherent STTCs for up to four transmit antennas, we see that they have similar performance deterioration to noncoherently demodulated M-PSK using a single antenna. Various simulations have been done to confirm the analysis.

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Katz, Ettie. „Trellis codes for multipath fading ISI channels with sequential detection“. Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/13908.

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Oruç, Özgür Altınkaya Mustafa Aziz. „Differential and coherent detection schemes for space-time block codes/“. [s.l.]: [s.n.], 2002. http://library.iyte.edu.tr/tezler/master/elektrikveelektronikmuh/T000133.pdf.

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Knopp, Raymond. „Module-phase-codes with non-coherent detection and reduced-complexity decoding“. Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68034.

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This thesis considers M-ary phase coding for the non-coherent AWGN channel. More precisely, we develop block-coded MPSK modulation schemes specifically for non-coherent block detection which significantly surpass the performance of ideal uncoded coherent MPSK. A class of block codes which are well-matched to MPSK modulation, called module-phase codes, is presented. The algebraic framework used for defining these codes relies on elements of module theory which are discussed along with a method for constructing such codes for non-coherent detection. It is shown that differential encoding, when considered on a block basis, may be viewed as a specific code from a particular class of module-phase codes. Two classes of more powerful codes which achieve significant coding gain with respect to coherent detection of uncoded MPSK are presented. In the first class of module-phase codes, the coding gain is achieved at the expense of bandwidth expansion. In the second class, however, the coding gain is achieved at the expense of signal constellation expansion without expanding bandwidth. A reduced-complexity/sub-optimal decoding strategy based on a modification of information set decoding is described. Its performance is analysed through the use of computer simulations for various different codes. Finally, we address the performance of these codes combined with the reduced-complexity decoding method over correlated Rayleigh fading channels.

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Valenti, Matthew C. „Iterative Detection and Decoding for Wireless Communications“. Diss., Virginia Tech, 1999. http://hdl.handle.net/10919/28290.

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Turbo codes are a class of forward error correction (FEC) codes that offer energy efficiencies close to the limits predicted by information theory. The features of turbo codes include parallel code concatenation, recursive convolutional encoding, nonuniform interleaving, and an associated iterative decoding algorithm. Although the iterative decoding algorithm has been primarily used for the decoding of turbo codes, it represents a solution to a more general class of estimation problems that can be described as follows: a data set directly or indirectly drives the state transitions of two or more Markov processes; the output of one or more of the Markov processes is observed through noise; based on the observations, the original data set is estimated. This dissertation specifically describes the process of encoding and decoding turbo codes. In addition, a more general discussion of iterative decoding is presented. Then, several new applications of iterative decoding are proposed and investigated through computer simulation. The new applications solve two categories of problems: the detection of turbo codes over time-varying channels, and the distributed detection of coded multiple-access signals. Because turbo codes operate at low signal-to-noise ratios, the process of phase estimation and tracking becomes difficult to perform. Additionally, the turbo decoding algorithm requires precise estimates of the channel gain and noise variance. The first significant contribution of this dissertation is a study of several methods of channel estimation suitable specifically for turbo coded systems. The second significant contribution of this dissertation is a proposed method for jointly detecting coded multiple-access signals using observations from several locations, such as spatially separated base stations. The proposed system architecture draws from the concepts of macrodiversity combining, multiuser detection, and iterative decoding. Simulation results show that when the system is applied to the time division multiple-access cellular uplink, a significant improvement in system capacity results.
Ph. D.

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Xu, Chang. „Inconsistency detection and resolution for context-aware pervasive computing /“. View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20XU.

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Albayrak, Aras. „Automatic Pose and Position Estimation by Using Spiral Codes“. Thesis, Högskolan i Halmstad, Halmstad Embedded and Intelligent Systems Research (EIS), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-27175.

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This master thesis is about providing the implementation of synthesis, detection of spiral symbols and estimating the pan/tilt angle and position by using camera calibration. The focus is however on the latter, the estimation of parameters of localization. Spiral symbols are used to be able to give an object an identity as well as to locate it. Due to the spiral symbol´s characteristic shape, we can use the generalized structure tensor (GST) algorithm which is particularly efficient to detect different members of the spiral family. Once we detect spirals, we know the position and identity parameters of the spirals within an apriori known geometric configuration (on a sheet of paper). In turn, this information can be used to estimate the 3D-position and orientation of the object on which spirals are attached using a camera calibration method. This thesis provides an insight into how automatic detection of spirals attached on a sheet of paper, and from this, automatic deduction of position and pose parameters of the sheet, can be achieved by using a network camera. GST algorithm has an advantage of running the processes of detection of spirals efficiently w.r.t detection performance and computational resources because it uses a spiral image model well adapted to spiral spatial frequency characteristic. We report results on how detection is affected by zoom parameters of the network camera, as well as by the GST parameters; such as filter size. After all spirals centers are located and identified w.r.t. their twist/bending parameter, a flexible technique for camera calibration, proposed by Zhengyou Zhang implemented in Matlab within the present study, is performed. The performance of the position and pose estimation in 3D is reported. The main conclusion is, we have reasonable surface angle estimations for images which were taken by a WLAN network camera in different conditions such as different illumination and different distances.

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Bücher zum Thema "Detection codes"

Kløve, Torleiv. Codes for error detection. Singapore: World Scientific, 2007.

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Gössel, Michael. Error detection circuits. London: McGraw-Hill, 1993.

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Crow, Judy. Model-based reconfiguration: Diagnosis and recovery. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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Leacock, Claudia. Automated grammatical error detection for language learners. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2010.

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Thompson, Michael W. Concatenated coding using trellis-coded modulation: Final report : NAG 9-767. [Washington, DC: National Aeronautics and Space Administration, 1997.

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Freeman, Jon C. Introduction to forward-error-correcting coding. Washington D.C: NationalAeronautics and Space Administration, Office of Management, Scientific and Technical Information Branch, 1996.

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Freeman, Jon C. Introduction to forward-error-correcting coding. Cleveland, Ohio: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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Kløve, Torleiv, und Valery I. Korzhik. Error Detecting Codes. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-2309-3.

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Buchteile zum Thema "Detection codes"

Gonzalez, Diego L. „Error Detection and Correction Codes“. In Biosemiotics, 379–94. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6340-4_17.

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Wu, Zining. „Turbo Codes and Turbo Equalization“. In Coding and Iterative Detection for Magnetic Recording Channels, 21–46. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4565-1_2.

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Wu, Zining. „Low-Density Parity-Check Codes“. In Coding and Iterative Detection for Magnetic Recording Channels, 47–69. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4565-1_3.

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Elkhadir, Zyad, Khalid Chougdali und Mohammed Benattou. „A Median Nearest Neighbors LDA for Anomaly Network Detection“. In Codes, Cryptology and Information Security, 128–41. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55589-8_9.

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Jafargholi, Zahra, und Daniel Wichs. „Tamper Detection and Continuous Non-malleable Codes“. In Theory of Cryptography, 451–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46494-6_19.

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Wu, Zining. „Interleaved Parity Check Codes and Reduced Complexity Detection“. In Coding and Iterative Detection for Magnetic Recording Channels, 103–17. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4565-1_5.

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Lugiez, Denis. „Multivariate polynomial factoring and detection of true factors“. In Applied Algebra, Algorithmics and Error-Correcting Codes, 169–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/3-540-16767-6_62.

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Methods, Algebraic, und F. S. Vainstein. „Error detection and correction in numerical computations“. In Applied Algebra, Algebraic Algorithms and Error-Correcting Codes, 456–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54522-0_133.

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Lin, Fuchun, Reihaneh Safavi-Naini und Pengwei Wang. „Codes for Detection of Limited View Algebraic Tampering“. In Information Security and Cryptology, 309–20. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54705-3_19.

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Pintus, Maurizio. „Analysis of Neural Codes for Near-Duplicate Detection“. In Advanced Concepts for Intelligent Vision Systems, 357–68. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01449-0_30.

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Konferenzberichte zum Thema "Detection codes"

Giard, Pascal, Alexios Balatsoukas-Stimming und Andreas Burg. „Blind detection of polar codes“. In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). IEEE, 2017. http://dx.doi.org/10.1109/sips.2017.8109977.

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Picard, Justin, Paul Landry und Michael Bolay. „Counterfeit detection with QR codes“. In DocEng '21: ACM Symposium on Document Engineering 2021. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3469096.3474924.

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Qi, Gang, Xiaoli Yang und Wei Fan. „LDPC codes in wireless optical communication application“. In ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, herausgegeben von Keith E. Wilson, Jing Ma, Liren Liu, Huilin Jiang und Xizheng Ke. SPIE, 2013. http://dx.doi.org/10.1117/12.2031610.

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Sobron, Iker, Maitane Barrenechea, Pello Ochandiano, Lorena Martinez, Mikel Mendicute und Jon Altuna. „Low-complexity detection of golden codes in LDPC-coded OFDM systems“. In ICASSP 2011 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2011. http://dx.doi.org/10.1109/icassp.2011.5946692.

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Arslan, Suayb S., Jaewook Lee und Turguy Goker. „Embedding Noise Prediction Into List-Viterbi Decoding Using Error Detection Codes for Magnetic Tape Systems“. In ASME 2013 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/isps2013-2835.

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A List–Viterbi detector produces a rank ordered list of the N globally best candidates in a trellis search. A List–Viterbi detector structure is proposed that incorporates the noise prediction with periodic state-metric updates based on outer error detection codes (EDCs). More specifically, a periodic decision making process is utilized for a non-overlapping sliding windows of P bits based on the use of outer EDCs. In a number of magnetic recording applications, Error Correction Coding (ECC) is adversely effected by the presence of long and dominant error events. Unlike the conventional post processing methods that are usually tailored to a specific set of dominant error events or the joint modulation code trellis architectures that are operating on larger state spaces at the expense of increased implementation complexity, the proposed detector does not use any a priori information about the error event distributions and operates at reduced state trellis. We present pre-ECC bit error rate performance as well as the post-ECC codeword failure rates of the proposed detector using perfect detection scenario as well as practical detection codes as the EDCs are not essential to the overall design. Furthermore, it is observed that proposed algorithm does not introduce new error events. Simulation results show that the proposed algorithm gives improved bit error and post-ECC codeword failure rates at the expense of some increase in complexity.

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Naydenova, Irina, und Torleiv Klove. „Large proper codes for error detection“. In 2006 IEEE Information Theory Workshop - ITW '06 Chengdu. IEEE, 2006. http://dx.doi.org/10.1109/itw2.2006.323781.

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Zhen Wang, Mark Karpovsky und Berk Sunar. „Multilinear codes for robust error detection“. In 2009 15th IEEE International On-Line Testing Symposium (IOLTS 2009). IEEE, 2009. http://dx.doi.org/10.1109/iolts.2009.5196002.

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Pingping Shang, Sooyoung Kim und Kwonhue Choi. „Soft ZF MIMO detection for turbo codes“. In 2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). IEEE, 2010. http://dx.doi.org/10.1109/wimob.2010.5644980.

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Ren, Xiaofeng, und Deva Ramanan. „Histograms of Sparse Codes for Object Detection“. In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2013. http://dx.doi.org/10.1109/cvpr.2013.417.

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Moon, J. J., und L. R. Carley. „Sequeuce detection on run-length-limited codes“. In Twenty-Third Asilomar Conference on Signals, Systems and Computers, 1989. IEEE, 1989. http://dx.doi.org/10.1109/acssc.1989.1200834.

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Berichte der Organisationen zum Thema "Detection codes"

Wolf, Jack K. A Study of Error Detection and Correction Codes. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada162196.

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Heinstein, M. W., S. W. Attaway, J. W. Swegle und F. J. Mello. A general-purpose contact detection algorithm for nonlinear structural analysis codes. Office of Scientific and Technical Information (OSTI), Mai 1993. http://dx.doi.org/10.2172/10175733.

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May, Elebeoba Eni, Mark Daniel Rintoul, Anna Marie Johnston, Richard J. Pryor, William Eugene Hart und Jean-Paul Watson. Detection and reconstruction of error control codes for engineered and biological regulatory systems. Office of Scientific and Technical Information (OSTI), Oktober 2003. http://dx.doi.org/10.2172/918239.

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Viterbi, Andrew J., Jack K. Wolf, Lyle J. Fredrickson, Jeff A. Levin und Robert D. Blakeney. Research in Mathematics and Computer Science: Calculation of the Probability of Undetected Error for Certain Error Detection Codes. Phase 2. Fort Belvoir, VA: Defense Technical Information Center, Mai 1991. http://dx.doi.org/10.21236/ada238234.

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Crawford, R., P. Kerchen, K. Levitt, R. Olsson, M. Archer und M. Casillas. Automated assistance for detecting malicious code. Office of Scientific and Technical Information (OSTI), Juni 1993. http://dx.doi.org/10.2172/10176903.

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Spielman, R. X-Ray Detector: An x-ray radiation detector design code. Office of Scientific and Technical Information (OSTI), April 1990. http://dx.doi.org/10.2172/6908044.

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Shaver, Mark W., Andrew M. Casella, Richard S. Wittman und John W. Hayes. Evaluation and Testing of the ADVANTG Code on SNM Detection. Office of Scientific and Technical Information (OSTI), September 2013. http://dx.doi.org/10.2172/1096695.

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Gentry, S. M. Detection optimization using linear systems analysis of a coded aperture laser sensor system. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/10187583.

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Neogi, Orgho. Search for Dark Matter in a Coannihilation Codex Model With CMS Detector. Office of Scientific and Technical Information (OSTI), November 2018. http://dx.doi.org/10.2172/1496031.

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Wen, Qingsong, Minzhen Ren und Xiaoli Ma. Fixed-point Design of the Lattice-reduction-aided Iterative Detection and Decoding Receiver for Coded MIMO Systems. Fort Belvoir, VA: Defense Technical Information Center, Januar 2011. http://dx.doi.org/10.21236/ada586964.

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