Relevant bibliographies by topics / Error-correction

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Error-correction'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Error-correction"

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M. Venkataramanamma, M. Venkataramanamma, and U. Kalpana Reddy. "Multiple Error Correction Controlling." International Journal of Scientific Research 2, no. 10 (June 1, 2012): 1–3. http://dx.doi.org/10.15373/22778179/oct2013/55.

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Fulvio, J. M., and P. R. Schrater. "When is error-correction just error-correction?" Journal of Vision 12, no. 9 (August 10, 2012): 831. http://dx.doi.org/10.1167/12.9.831.

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Xinling, MA. "Error Correction." Acta Mechanica Sinica 20, no. 1 (February 2004): 45. http://dx.doi.org/10.1007/bf02493570.

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Jianzhong, LIN. "Error Correction." Acta Mechanica Sinica 20, no. 1 (February 2004): 45. http://dx.doi.org/10.1007/bf02493571.

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Xinling, MA. "Error Correction." Acta Mechanica Sinica 20, no. 1 (February 2004): 45. http://dx.doi.org/10.1007/bf02484243.

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Babaeva, Vasila. "Error Classification And Methods Of Their Correction." American Journal of Social Science and Education Innovations 02, no. 08 (August 29, 2020): 474–77. http://dx.doi.org/10.37547/tajssei/volume02issue08-76.

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Jun, Ho-yoon, and Yong-surk Lee. "Single error correction, double error detection and double adjacent error correction with no mis-correction code." IEICE Electronics Express 10, no. 20 (2013): 20130743. http://dx.doi.org/10.1587/elex.10.20130743.

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Lin, Laura, Stephen P. Hale, and Paul Schimmel. "Aminoacylation error correction." Nature 384, no. 6604 (November 1996): 33–34. http://dx.doi.org/10.1038/384033b0.

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Paz, Juan Pablo, and Wojciech Hubert Zurek. "Continuous error correction." Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 454, no. 1969 (January 8, 1998): 355–64. http://dx.doi.org/10.1098/rspa.1998.0165.

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Llewellyn, Hilary A. "Algebraic Error Correction." Medical Decision Making 10, no. 2 (June 1990): 148–49. http://dx.doi.org/10.1177/0272989x9001000211.

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Dissertations / Theses on the topic "Error-correction"

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Almlöf, Jonas. "Quantum error correction." Licentiate thesis, KTH, Kvantelektronik och -optik, QEO, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-106795.

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This thesis intends to familiarise the reader with quantum error correction, and also show some relations to the well known concept of information - and the lesser known quantum information. Quantum information describes how information can be carried by quantum states, and how interaction with other systems give rise to a full set of quantum phenomena, many of which have no correspondence in classical information theory. These phenomena include decoherence, as a consequence of entanglement. Decoherence can also be understood as "information leakage", i.e., knowledge of an event is transferred to the reservoir - an effect that in general destroys superpositions of pure states. It is possible to protect quantum states (e.g., qubits) from interaction with the environment - but not by amplification or duplication, due to the "no-cloning" theorem. Instead, this is done using coding, non-demolition measurements, and recovery operations. In a typical scenario, however, not all types of destructive events are likely to occur, but only those allowed by the information carrier, the type of interaction with the environment, and how the environment "picks up" information of the error events. These characteristics can be incorporated into a code, i.e., a channel-adapted quantum error-correcting code. Often, it is assumed that the environment's ability to distinguish between error events is small, and I will denote such environments "memory-less".  This assumption is not always valid, since the ability to distinguish error events is related to the \emph{temperature} of the environment, and in the particular case of information coded onto photons,  typically holds, and one must then assume that the environment has a "memory". In this thesis, I describe a short quantum error-correcting code (QECC), adapted for photons interacting with a cold environment, i.e., this code protects from an environment that continuously records which error occurred in the coded quantum state. Also, it is of interest to compare the performance of different QECCs - But which yardstick should one use? We compare two such figures of merit, namely the quantum mutual information and the quantum fidelity, and show that they can not, in general, be simultaneously maximised in an error correcting procedure. To show this, we have used a five-qubit perfect code, but assumed a channel that only cause bit-flip errors. It appears that quantum mutual information is the better suited yardstick of the two, however more tedious to calculate than quantum fidelity - which is more commonly used.
Denna avhandling är en introduktion till kvantfelrättning, där jag undersöker släktskapet med teorin om klassisk information - men också det mindre välkända området kvantinformation. Kvantinformation beskriver hur information kan bäras av kvanttillstånd, och hur växelverkan med andra system ger upphov till åtskilliga typer av fel och effekter, varav många saknar motsvarighet i den klassiska informationsteorin. Bland dessa effekter återfinns dekoherens - en konsekvens av s.k. sammanflätning. Dekoherens kan också förstås som "informationsläckage", det vill säga att kunskap om en händelse överförs till omgivningen - en effekt som i allmänhet förstör superpositioner i rena kvanttillstånd.  Det är möjligt att med hjälp av kvantfelrättning skydda kvanttillstånd (t.ex. qubitar) från omgivningens påverkan, dock kan sådana tillstånd aldrig förstärkas eller dupliceras, p.g.a icke-kloningsteoremet. Tillstånden skyddas genom att införa redundans, varpå tillstånden interagerar med omgivningen. Felen identifieras m.h.a. icke-förstörande mätningar och återställs med unitära grindar och ancilla-tillstånd.Men i realiteten kommer inte alla tänkbara fel att inträffa, utan dessa begränsas av vilken informationsbärare som används, vilken interaktion som uppstår med omgivningen, samt hur omgivningen "fångar upp" information om felhändelserna. Med kunskap om sådan karakteristik kan man bygga koder, s.k. kanalanpassade kvantfelrättande koder. Vanligtvis antas att omgivningens förmåga att särskilja felhändelser är liten, och man kan då tala om en minneslös omgivning. Antagandet gäller inte alltid, då denna förmåga bestäms av reservoirens temperatur, och i det speciella fall då fotoner används som informationsbärare gäller typiskt , och vi måste anta att reservoiren faktiskt har ett "minne". I avhandlingen beskrivs en kort, kvantfelrättande kod som är anpassad för fotoner i växelverkan med en "kall" omgivning, d.v.s. denna kod skyddar mot en omgivning som kontinuerligt registrerar vilket fel som uppstått i det kodade tillståndet.  Det är också av stort intresse att kunna jämföra prestanda hos kvantfelrättande koder, utifrån någon slags "måttstock" - men vilken? Jag jämför två sådana mått, nämligen ömsesidig kvantinformation, samt kvantfidelitet, och visar att dessa i allmänhet inte kan maximeras samtidigt i en felrättningsprocedur. För att visa detta har en 5-qubitarskod använts i en tänkt kanal där bara bitflip-fel uppstår, och utrymme därför finns att detektera fel. Ömsesidig kvantinformation framstår som det bättre måttet, dock är detta mått betydligt mer arbetskrävande att beräkna, än kvantfidelitet - som är det mest förekommande måttet.

QC 20121206

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Peikert, Christopher Jason. "Cryptographic error correction." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38320.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (leaves 67-71).
It has been said that "cryptography is about concealing information, and coding theory is about revealing it." Despite these apparently conflicting goals, the two fields have common origins and many interesting relationships. In this thesis, we establish new connections between cryptography and coding theory in two ways: first, by applying cryptographic tools to solve classical problems from the theory of error correction; and second, by studying special kinds of codes that are motivated by cryptographic applications. In the first part of this thesis, we consider a model of error correction in which the source of errors is adversarial, but limited to feasible computation. In this model, we construct appealingly simple, general, and efficient cryptographic coding schemes which can recover from much larger error rates than schemes for classical models of adversarial noise. In the second part, we study collusion-secure fingerprinting codes, which are of fundamental importance in cryptographic applications like data watermarking and traitor tracing. We demonstrate tight lower bounds on the lengths of such codes by devising and analyzing a general collusive attack that works for any code.
by Christopher Jason Peikert.
Ph.D.
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Almlöf, Jonas. "Quantum error correction." Doctoral thesis, KTH, Kvantelektronik och -optik, QEO, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-180533.

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Quantum error correction is the art of protecting quantum states from the detrimental influence from the environment. To master this art, one must understand how the system interacts with the environment and gives rise to a full set of quantum phenomena, many of which have no correspondence in classical information theory. Such phenomena include decoherence, an effect that in general destroys superpositions of pure states as a consequence of entanglement with the environment. But decoherence can also be understood as “information leakage”, i.e., when knowledge of an encoded code block is transferred to the environment. In this event, the block’s information or entanglement content is typically lost. In a typical scenario, however, not all types of destructive events are likely to occur, but only those allowed by the information carrier, the type of interaction with the environment, and how the environment “picks up” information of the error events. These characteristics can be incorporated into a code, i.e., a channel-adapted quantum error-correcting code. Often, it is assumed that the environment’s ability to distinguish between error events is small, and I will denote such environments “memory-less”. But this assumption is not always valid, since the ability to distinguish error events is related to the temperature of the environment, and in the particular case of information coded onto photons, kBTR «ℏω typically holds, and one must then assume that the environment has a “memory”. In the thesis I describe a short quantum error-correction code adapted for photons interacting with a “cold” reservoir, i.e., a reservoir which continuously probes what error occurred in the coded state. I also study other types of environments, and show how to distill meaningful figures of merit from codes adapted for these channels, as it turns out that resource-based figures reflecting both information and entanglement can be calculated exactly for a well-studied class of channels: the Pauli channels. Starting from these resource-based figures, I establish the notion of efficiency and quality and show that there will be a trade-off between efficiency and quality for short codes. Finally I show how to incorporate, into these calculations, the choices one has to make when handling quantum states that have been detected as incorrect, but where no prospect of correcting them exists, i.e., so-called detection errors.

QC 20160115

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Ng, Wing-han Christina. "Does error correction lead to error reduction?" Thesis, Hong Kong : University of Hong Kong, 2002. http://sunzi.lib.hku.hk/hkuto/record.jsp?B26173347.

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Jeffs, Stephen David. "Error correction in memory /." Title page, table of contents and abstract only, 2004. http://web4.library.adelaide.edu.au/theses/09ARPS/09arpsj474.pdf.

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Zhang, Wenbo. "Unary error correction coding." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/419401/.

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In this thesis, we introduce the novel concept of Unary Error Correction (UEC) coding. Our UEC code is a Joint Source and Channel Coding (JSCC) scheme conceived for performing both the compression and error correction of multimedia information during its transmission from an encoder to a decoder. The UEC encoder generates a bit sequence by concatenating and encoding unary codewords, while the decoder operates on the basis of a trellis that has only a modest complexity, even when the source symbol values are selected from a set having an infinite cardinality, such as the set of all positive integers. This trellis is designed so that the transitions between its states are synchronous with the transitions between the consecutive unary codewords in the concatenated bit sequence. This allows the UEC decoder to exploit any residual redundancy that remains following UEC encoding for the purpose of error correction by using the classic Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm. Owing to this, the UEC code is capable of mitigating any potential capacity loss, hence facilitating near-capacity operation, even when the cardinality of the symbol value set is infinite. We investigate the applications, characteristics and performance of the UEC code in the context of digital telecommunications. Firstly, we propose an adaptive UEC design for expediting the decoding process. By concatenating the UEC code with a turbo code, we conceive a three-stage concatenated adaptive iterative decoding technique. A Three-Dimensional (3D) EXtrinsic Information Transfer (EXIT) chart technique is proposed for both controlling the dynamic adaptation of the UEC trellis decoder, as well as for controlling the activation order between the UEC decoder and the turbo decoder. Secondly, we develop an irregular UEC design for ‘nearer-capacity’ operation. The irregular scheme employs different UEC parametrizations for the coding of different subsets of each message frame, operating on the basis of a single irregular trellis having a novel structure. This allows the irregularity to be controlled on a fine-grained bit-by-bit basis, rather than on a symbol-by-symbol basis. Hence, nearer-to-capacity operation is facilitated by exploiting this fine-grained control of the irregularity. Thirdly, we propose a learning-aided UEC design for transmitting symbol values selected from unknown and non-stationary probability distributions. The learning-aided UEC scheme is capable of heuristically inferring the source symbol distribution, hence eliminating the requirement of any prior knowledge of the symbol occurrence probabilities at either the transmitter or the receiver. This is achieved by inferring the source distribution based on the received symbols and by feeding this information back to the decoder. In this way, the quality of the recovered symbols and the estimate of the source distribution can be gradually improved in successive frames, hence allowing reliable near-capacity operation to be achieved, even if the source is unknown and non-stationary. Finally, we demonstrate that the research illustrated in this thesis can be extended in several directions, by highlighting a number of opportunities for future work. The techniques proposed for enhancing the UEC code can be extended to the Rice Error Correction (RiceEC) code, to the Elias Gamma Error Correction (EGEC) code and to the Exponential Golomb Error Correction (ExpGEC) code. In this way, our UEC scheme may be extended to the family of universal error correction codes, which facilitate the nearcapacity transmission of infinite-cardinality symbol alphabets having any arbitrary monotonic probability distribution, as well as providing a wider range of applications. With these benefits, this thesis may contribute to future standards for the reliable near-capacity transmission of multimedia information, having significant technical and economic impact.
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Babar, Zunaira. "Quantum error correction codes." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/380165/.

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Quantum parallel processing techniques are capable of solving certain complex problems at a substantially lower complexity than their classical counterparts. From the perspective of telecommunications, this quantum-domain parallel processing provides a plausible solution for achieving full-search based multi-stream detection, which is vital for future gigabit-wireless systems. The peculiar laws of quantum mechanics have also spurred interest in the absolutely secure quantum-based communication systems. Unfortunately, quantum decoherence imposes a hitherto insurmountable impairment on the practical implementation of quantum computation as well as on quantum communication systems, which may be overcome with the aid of efficient error correction codes. In this thesis, we design error correction codes for the quantum domain, which is an intricate journey from the realm of classical channel coding theory to that of the Quantum Error Correction Codes (QECCs). Since quantum-based communication systems are capable of supporting the transmission of both classical and quantum information, we initially focus our attention on the code design for entanglementassisted classical communication over the quantum depolarizing channel. We conceive an Extrinsic Information Transfer (EXIT) chart aided near-capacity classical-quantum code design, which invokes a classical Irregular Convolutional Code (IRCC) and a Unity Rate Code (URC) in conjunction with our proposed soft-decision aided SuperDense Code (SD). Hence, it is referred to as an ‘IRCC-URCSD’ arrangement. The proposed scheme is intrinsically amalgamated both with 2-qubit as well as 3-qubit SD coding protocols and it is benchmarked against the corresponding entanglement-assisted classical capacity. Since the IRCC-URC-SD scheme is a bit-based design, it incurs a capacity loss. As a further advance, we design a symbol based concatenated code design, referred to as a symbol-based ‘CC-URC-SD’, which relies on a single-component classical Convolutional Code (CC). Additionally, for the sake of reducing the associated decoding complexity, we also investigate the impact of the constraint length of the convolutional code on the achievable performance. Our initial designs, namely IRCC-URC-SD and CC-URC-SD, exploit redundancy in the classical domain. By contrast, QECCs relying on the quantum-domain redundancy are indispensable for conceiving a quantum communication system supporting the transmission of quantum information and also for quantum computing. Therefore, we next provide insights into the transformation from the family of classical codes to the class of quantum codes known as ‘Quantum Stabilizer Codes’ (QSC), which invoke the classical syndrome decoding. Particularly, we detail the underlying quantum-to classical isomorphism, which facilitates the design of meritorious families of QECCs from the known classical codes. We further study the syndrome decoding techniques operating over classical channels, which may be exploited for decoding QSCs. In this context, we conceive a syndrome-based block decoding approach for the classical Turbo Trellis Coded Modulation (TTCM), whose performance is investigated for transmission over an Additive White Gaussian Noise (AWGN) channel as well as over an uncorrelated Rayleigh fading channel. Pursuing our objective of designing efficient QECCs, we next consider the construction of Hashingbound-approaching concatenated quantum codes. In this quest, we appropriately adapt the conventional non-binary EXIT charts for Quantum Turbo Codes (QTCs) by exploiting the intrinsic quantumto- classical isomorphism. We further demonstrate the explicit benefit of our EXIT-chart technique for achieving a Hashing-bound-approaching code design. We also propose a generically applicable structure for Quantum Irregular Convolutional Codes (QIRCCs), which can be dynamically adapted to a specific application scenario with the aid of the EXIT charts. More explicitly, we provide a detailed design example by constructing a 10-subcode QIRCC and use it as an outer code in a concatenated quantum code structure for evaluating its performance. Working further in the direction of iterative code structures, we survey Quantum Low Density Parity Check (QLPDC) codes from the perspective of code design as well as in terms of their decoding algorithms. Furthermore, we propose a radically new class of high-rate row-circulant Quasi-Cyclic QLDPC (QC-QLDPC) codes, which can be constructed from arbitrary row-circulant classical QC LDPC matrices. We also conceive a modified non-binary decoding algorithm for homogeneous Calderbank-Shor-Steane (CSS)-type QLDPC codes, which is capable of alleviating the problems imposed by the unavoidable length-4 cycles. Our modified decoder outperforms the state-of-the-art decoders in terms of their Word Error Rate (WER) performance, despite imposing a reduced decoding complexity. Finally, we intricately amalgamate our modified decoder with the classic Uniformly-ReWeighted Belief Propagation (URW-BP) for the sake of achieving further performance improvement.
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Fiehler, Katja. "Temporospatial characteristics of error correction /." Leipzig ; München : MPI for Human Cognitive and Brain Sciences, 2004. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=013077731&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Fletcher, Andrew Stephen. "Channel-adapted quantum error correction." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40497.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (p. 159-163).
Quantum error correction (QEC) is an essential concept for any quantum information processing device. Typically, QEC is designed with minimal assumptions about the noise process; this generic assumption exacts a high cost in efficiency and performance. We examine QEC methods that are adapted to the physical noise model. In physical systems, errors are not likely to be arbitrary; rather we will have reasonable models for the structure of quantum decoherence. We may choose quantum error correcting codes and recovery operations that specifically target the most likely errors. This can increase QEC performance and also reduce the required overhead. We present a convex optimization method to determine the optimal (in terms of average entanglement fidelity) recovery operation for a given channel, encoding, and information source. This is solvable via a semidefinite program (SDP). We derive an analytic solution to the optimal recovery for the case of stabilizer codes, the completely mixed input source, and channels characterized by Pauli group errors. We present computational algorithms to generate near-optimal recovery operations structured to begin with a projective syndrome measurement.
(cont.) These structured operations are more computationally scalable than the SDP required for computing the optimal; we can thus numerically analyze longer codes. Using Lagrange duality, we bound the performance of the structured recovery operations and show that they are nearly optimal in many relevant cases. We present two classes of channel-adapted quantum error correcting codes specifically designed for the amplitude damping channel. These have significantly higher rates with shorter block lengths than corresponding generic quantum error correcting codes. Both classes are stabilizer codes, and have good fidelity performance with stabilizer recovery operations. The encoding, syndrome measurement, and syndrome recovery operations can all be implemented with Clifford group operations.
by Andrew Stephen Fletcher.
Ph.D.
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Wang, Tao. "Elias Gamma Error Correction Code." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/400268/.

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Shannon’s source-channel coding separation theorem states that near-capacity communication is theoretically possible, when employing Separate Source and Channel Codes (SSCCs), provided that an unlimited encoding/decoding delay and complexity can be afforded. However, it is typically impossible to remove all source redundancy with the aid of practical finite-delay and finite-complexity source encoding, which leads to capacity loss. As a potential remedy, Joint Source and Channel Codes (JSCCs) have been proposed for exploiting the residual redundancy and hence for avoiding any capacity loss. However, all previous JSCCs have been designed for representing symbols values that are selected from a set having a low cardinality and hence they suffer from an excessive decoding complexity, when the cardinality of the symbol value set is large, leading to an infinite complexity, when the cardinality is infinite. Motivated by this, we propose the family of Unary Error Correction (UEC), Elias Gamma Error Correction (EGEC) and Reordered Elias Gamma Error Correction (REGEC) codes in this thesis. Our family of codes belong to the JSCC class designed to have only a modest complexity that is independent of the cardinality of the symbol value set. We exemplify the application of each of the codes in the context of a serially concatenated iterative decoding scheme. In each coding scheme, the encoder generates a bit sequence by encoding and concatenating codewords, while the decoder performs iterative decoding using the classic Logarithmic Bahl, Cocke, Jelinek and Raviv (Log-BCJR) algorithm. Owing to this, our proposed codes are capable of mitigating any potential capacity loss, hence facilitating near-capacity operation. Our proposed UEC code is the first JSCC that maintains a low decoding complexity, when invoked for representing symbol values that are selected from a set having large or even infinite cardinality. The UEC trellis is designed to describe the unary codewords so that the transitions between its states are synchronous with the transitions between the consecutive codewords in the bit sequence. The unary code employed in the UEC code has a simple structure, which can be readily exploited for error correction without requiring an excessive number of trellis transitions and states. However, the UEC scheme has found limited applications, since the unary code is not a universal code. This motivates the design of our EGEC code, which is the first universal code in our code family. The EGEC code relies on trellis representation of the EG code, which is generated by decomposing each symbol into two sub-symbols, for the sake of simplifying the structure of the EG code. However, the reliance on these two parts requires us to carefully tailor the Unequal Protection (UEP) of the two parts for the specific source probability distribution encountered, whilst the actual source distribution may be unknown or non-stationary. Additionally, the complex structure of the EGEC code may impose further disadvantages associated with an increased decoding delay, loss of synchronisation, capacity loss and increased complexity due to puncturing. This motivates us to propose a universal JSCC REGEC code, which has a significantly simpler structure than the EGEC code. The proposed codes were benchmarked against SSCC benchmarkers throughout this thesis and they were found to offer significant gains in all cases. Finally, we demonstrate that our code family proposed in this thesis can be extended by several potential directions. The sophisticated techniques that have been subsequently proposed in the thesis for extending the UEC code, such as irregular trellis designs and the adaptive distribution-learning algorithm, can be readily applied to the REGEC codes which is an explicit benefit of its simple trellis structure. Furthermore, our proposed REGEC code can be extended using techniques that been subsequently proposed for extending the EGEC both to Rice Error Correction (RiceEC) codes and to Exponential Golomb Error Correction (ExpGEC) codes.
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Books on the topic "Error-correction"

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Lidar, Daniel A., Todd A. Brun, and Todd Brun, eds. Quantum Error Correction. Cambridge: Cambridge University Press, 2009. http://dx.doi.org/10.1017/cbo9781139034807.

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La Guardia, Giuliano Gadioli. Quantum Error Correction. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48551-1.

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Moon, Todd K. Error Correction Coding. New York: John Wiley & Sons, Ltd., 2005.

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Childs, Lindsay N. Cryptology and Error Correction. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15453-0.

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Urbain, Jean-Pierre. Exogeneity in Error Correction Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-95706-2.

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Guang, Xuan, and Zhen Zhang. Linear Network Error Correction Coding. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0588-1.

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Tomlinson, Martin, Cen Jung Tjhai, Marcel A. Ambroze, Mohammed Ahmed, and Mubarak Jibril. Error-Correction Coding and Decoding. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51103-0.

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Hylleberg, Svend. Cointegration and error correction mechanisms. Aarhus, Denmark: Institute of Economics, University of Aarhus, 1988.

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Urbain, Jean-Pierre. Exogeneity in error correction models. Berlin: Springer-Verlag, 1993.

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D, Ivancic William, and United States. National Aeronautics and Space Administration., eds. Multichannel error correction code decoder. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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Book chapters on the topic "Error-correction"

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Kao, Ming-Yang. "Error Correction." In Encyclopedia of Algorithms, 281. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_129.

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Weik, Martin H. "error correction." In Computer Science and Communications Dictionary, 538. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_6409.

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Charman, Tony, Susan Hepburn, Moira Lewis, Moira Lewis, Amanda Steiner, Sally J. Rogers, Annemarie Elburg, et al. "Error Correction." In Encyclopedia of Autism Spectrum Disorders, 1158–59. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_1292.

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Pritchard, Josh, and Mark Malady. "Error Correction." In Encyclopedia of Autism Spectrum Disorders, 1842–43. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-91280-6_1292.

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Scherer, Wolfgang. "Error Correction." In Mathematics of Quantum Computing, 343–402. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12358-1_7.

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La Guardia, Giuliano Gadioli. "Some Linear Algebra." In Quantum Error Correction, 1–16. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48551-1_1.

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La Guardia, Giuliano Gadioli. "A Little Bit of Quantum Mechanics." In Quantum Error Correction, 17–23. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48551-1_2.

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La Guardia, Giuliano Gadioli. "Quantum Error-Correcting Codes." In Quantum Error Correction, 25–41. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48551-1_3.

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La Guardia, Giuliano Gadioli. "Linear Block Codes." In Quantum Error Correction, 43–56. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48551-1_4.

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La Guardia, Giuliano Gadioli. "Quantum Code Constructions." In Quantum Error Correction, 57–124. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48551-1_5.

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Conference papers on the topic "Error-correction"

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Balli, Huseyin, Xijin Yan, and Zhen Zhang. "Error Correction Capability of Random Network Error Correction Codes." In 2007 IEEE International Symposium on Information Theory. IEEE, 2007. http://dx.doi.org/10.1109/isit.2007.4557447.

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Saiz-Adalid, Luis-J., Pedro Gil, Juan-Carlos Ruiz, Joaquin Gracia-Moran, Daniel Gil-Tomas, and J. Carlos Baraza-Calvo. "Ultrafast Error Correction Codes for Double Error Detection/Correction." In 2016 12th European Dependable Computing Conference (EDCC). IEEE, 2016. http://dx.doi.org/10.1109/edcc.2016.28.

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Lawrence, Steve, Kurt Bollacker, and C. Lee Giles. "Distributed error correction." In the fourth ACM conference. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/313238.313390.

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Cai, N., and R. W. Yeung. "Network error correction." In IEEE International Symposium on Information Theory, 2003. Proceedings. IEEE, 2003. http://dx.doi.org/10.1109/isit.2003.1228115.

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Luyi, Sui, Fu Jinyi, and Yang Xiaohua. "Forward Error Correction." In 2012 Fourth International Conference on Computational and Information Sciences (ICCIS). IEEE, 2012. http://dx.doi.org/10.1109/iccis.2012.158.

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Preskill, J. "Quantum error correction." In International Conference on Quantum Information. Washington, D.C.: OSA, 2001. http://dx.doi.org/10.1364/icqi.2001.t3.

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Pan, Fayu, and Bin Cao. "Efficient Grammatical Error Correction with Hierarchical Error Detections and Correction." In 2021 IEEE International Conference on Web Services (ICWS). IEEE, 2021. http://dx.doi.org/10.1109/icws53863.2021.00073.

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Sun, Rui, Xiuyu Wu, and Yunfang Wu. "An Error-Guided Correction Model for Chinese Spelling Error Correction." In Findings of the Association for Computational Linguistics: EMNLP 2022. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.findings-emnlp.278.

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Toyran, Mustafa, Thomas B. Pedersen, A. S. Atilla Hasekioglu, M. Ali Can, and Savas Berber. "Comparison of CASCADE error correction protocol and LDPC error correction codes." In 2012 20th Signal Processing and Communications Applications Conference (SIU). IEEE, 2012. http://dx.doi.org/10.1109/siu.2012.6204429.

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Dolgicers, Aleksandrs, and Jevgenijs Kozadajevs. "Current transformer error correction." In 2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC). IEEE, 2015. http://dx.doi.org/10.1109/eeeic.2015.7165347.

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Reports on the topic "Error-correction"

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Watson, M., A. Begen, and V. Roca. Forward Error Correction (FEC) Framework. RFC Editor, October 2011. http://dx.doi.org/10.17487/rfc6363.

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Park, Jong-kyu, Allen H. Boozer, Jonathan E. Menard, and Michael J. Schaffer. Error Field Correction in ITER. Office of Scientific and Technical Information (OSTI), May 2008. http://dx.doi.org/10.2172/959384.

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Uberti, J. WebRTC Forward Error Correction Requirements. RFC Editor, January 2021. http://dx.doi.org/10.17487/rfc8854.

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Luby, M., L. Vicisano, J. Gemmell, L. Rizzo, M. Handley, and J. Crowcroft. Forward Error Correction (FEC) Building Block. RFC Editor, December 2002. http://dx.doi.org/10.17487/rfc3452.

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Luby, M., and L. Vicisano. Compact Forward Error Correction (FEC) Schemes. RFC Editor, February 2004. http://dx.doi.org/10.17487/rfc3695.

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Watson, M., M. Luby, and L. Vicisano. Forward Error Correction (FEC) Building Block. RFC Editor, August 2007. http://dx.doi.org/10.17487/rfc5052.

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Watson, M. Basic Forward Error Correction (FEC) Schemes. RFC Editor, March 2009. http://dx.doi.org/10.17487/rfc5445.

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Lidar, Daniel, and Aephraim Steinberg. Underlying Information Technology Tailored Quantum Error Correction. Fort Belvoir, VA: Defense Technical Information Center, July 2006. http://dx.doi.org/10.21236/ada455920.

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Lacan, J., V. Roca, J. Peltotalo, and S. Peltotalo. Reed-Solomon Forward Error Correction (FEC) Schemes. RFC Editor, April 2009. http://dx.doi.org/10.17487/rfc5510.

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Mitkas, Pericles A. Error Detection and Correction for Optical Memories. Fort Belvoir, VA: Defense Technical Information Center, June 1997. http://dx.doi.org/10.21236/ada329310.

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