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Academic literature on the topic 'Error detection algorithms'

Author: Grafiati

Published: 28 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Error detection algorithms"

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Liu, Qing Min, Xue Li, and L. Zhang. "Realization Method for Detection on Arc Based on CCD." Applied Mechanics and Materials 687-691 (November 2014): 856–60. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.856.

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s: Arc detection is difficult for processing, assembly and testing of industrial production because of limitations of detection methods, algorithms and instruments. The least-squares algorithm is used to fit data in circle detection. The application of conventional least-squares algorithm is limited, as roundness error is bigger, precision is lower. For detecting arc with data points of non-uniform distribution, improved least-squares algorithm, developed an analysis algorithm for assessing the minimum zone roundness error. Center and radius can be solved, without iteration and truncation error. Using the discrete data instances verified different roundness error evaluation methods. Visual measurements have been carried out using the proposed methods. Calculated results using the four kinds of roundness error evaluation methods (Figure 7-10). Ball diameter errors are-0.0245mm、0.0176mm、-0.1052mm and 0.302mm, roundness errors are 0.07mm、0.063mm、0.078mm and 0.146mm. The improved least-squares algorithm and the minimum zone algorithm are suitable for distributed data of all kinds situations, particularly suitable for the realization of machine vision inspection system, fast speed, high precision, wide application.

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Abdulsattar, Ruaa Alaadeen, and Nada Hussein M. Ali. "Lookup Table Algorithm for Error Correction in Color Images." JOIV : International Journal on Informatics Visualization 2, no. 2 (March 3, 2018): 63. http://dx.doi.org/10.30630/joiv.2.2.113.

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Error correction and error detection techniques are often used in wireless transmission systems. A color image of type BMP is considered as an application of developed lookup table algorithms to detect and correct errors in these images. Decimal Matrix Code (DMC) and Hamming code (HC) techniques were integrated to compose Hybrid Matrix Code (HMC) to maximize the error detection and correction. The results obtained from HMC still have some error not corrected because the redundant bits added by Hamming codes to the data are considered inadequate, and it is suitable when the error rate is low for detection and correction processes. Besides, a Hamming code could not detect large burst error period, in addition, the have same values sometimes which lead to not detect the error and consequently increase the error ratio. The proposed algorithm LUT_CORR is presented to detect and correct errors in color images over noisy channels, the proposed algorithm depends on the parallel Cyclic Redundancy Code (CRC) method that's based on two algorithms: Sarwate and slicing By N algorithms. The LUT-CORR and the aforementioned algorithms were merged to correct errors in color images, the output results correct the corrupted images with a 100 % ratio almost. The above high correction ratio due to some unique values that the LUT-CORR algorithm have. The HMC and the proposed algorithm applied to different BMP images, the obtained results from LUT-CORR are compared to HMC for both Mean Square Error (MSE) and correction ratio. The outcome from the proposed algorithm shows a good performance and has a high correction ratio to retrieve the source BMP image.

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Morisette, Jeffrey T., Louis Giglio, Ivan Csiszar, Alberto Setzer, Wilfrid Schroeder, Douglas Morton, and Christopher O. Justice. "Validation of MODIS Active Fire Detection Products Derived from Two Algorithms." Earth Interactions 9, no. 9 (July 1, 2005): 1–25. http://dx.doi.org/10.1175/ei141.1.

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Abstract Fire influences global change and tropical ecosystems through its connection to land-cover dynamics, atmospheric composition, and the global carbon cycle. As such, the climate change community, the Brazilian government, and the Large-Scale Biosphere–Atmosphere (LBA) Experiment in Amazonia are interested in the use of satellites to monitor and quantify fire occurrence throughout Brazil. Because multiple satellites and algorithms are being utilized, it is important to quantify the accuracy of the derived products. In this paper the characteristics of two fire detection algorithms are evaluated, both of which are applied to Terra’s Moderate Resolution Imagine Spectroradiometer (MODIS) data and with both operationally producing publicly available fire locations. The two algorithms are NASA’s operational Earth Observing System (EOS) MODIS fire detection product and Brazil’s Instituto Nacional de Pesquisas Espaciais (INPE) algorithm. Both algorithms are compared to fire maps that are derived independently from 30-m spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. A quantitative comparison is accomplished through logistic regression and error matrices. Results show that the likelihood of MODIS fire detection, for either algorithm, is a function of both the number of ASTER fire pixels within the MODIS pixel as well as the contiguity of those pixels. Both algorithms have similar omission errors and each has a fairly high likelihood of detecting relatively small fires, as observed in the ASTER data. However, INPE’s commission error is roughly 3 times more than that of the EOS algorithm.

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Nguyen, G. D. "Error-detection codes: algorithms and fast implementation." IEEE Transactions on Computers 54, no. 1 (January 2005): 1–11. http://dx.doi.org/10.1109/tc.2005.7.

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Toghuj, Wael, and Ghazi I. Alkhatib. "Improved Algorithm for Error Correction." International Journal of Information Technology and Web Engineering 6, no. 1 (January 2011): 1–12. http://dx.doi.org/10.4018/jitwe.2011010101.

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Digital communication systems are an important part of modern society, and they rely on computers and networks to achieve critical tasks. Critical tasks require systems with a high level of reliability that can provide continuous correct operations. This paper presents a new algorithm for data encoding and decoding using a two-dimensional code that can be implemented in digital communication systems, electronic memories (DRAMs and SRAMs), and web engineering. The developed algorithms correct three errors in codeword and detect four, reaching an acceptable performance level. The program that is based on these algorithms enables the modeling of error detection and correction processes, optimizes the redundancy of the code, monitors the decoding procedures, and defines the speed of execution. The performance of the derived code improves error detection and correction over the classical code and with less complexity. Several extensible applications of the algorithms are also given.

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Kari, Lila, Stavros Konstantinidis, Steffen Kopecki, and Meng Yang. "Efficient Algorithms for Computing the Inner Edit Distance of a Regular Language via Transducers." Algorithms 11, no. 11 (October 23, 2018): 165. http://dx.doi.org/10.3390/a11110165.

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The concept of edit distance and its variants has applications in many areas such as computational linguistics, bioinformatics, and synchronization error detection in data communications. Here, we revisit the problem of computing the inner edit distance of a regular language given via a Nondeterministic Finite Automaton (NFA). This problem relates to the inherent maximal error-detecting capability of the language in question. We present two efficient algorithms for solving this problem, both of which execute in time O ( r 2 n 2 d ) , where r is the cardinality of the alphabet involved, n is the number of transitions in the given NFA, and d is the computed edit distance. We have implemented one of the two algorithms and present here a set of performance tests. The correctness of the algorithms is based on the connection between word distances and error detection and the fact that nondeterministic transducers can be used to represent the errors (resp., edit operations) involved in error-detection (resp., in word distances).

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Zhu, Yongkuan, Gurjot Singh Gaba, Fahad M. Almansour, Roobaea Alroobaea, and Mehedi Masud. "Application of data mining technology in detecting network intrusion and security maintenance." Journal of Intelligent Systems 30, no. 1 (January 1, 2021): 664–76. http://dx.doi.org/10.1515/jisys-2020-0146.

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Abstract In order to correct the deficiencies of intrusion detection technology, the entire computer and network security system are needed to be more perfect. This work proposes an improved k-means algorithm and an improved Apriori algorithm applied in data mining technology to detect network intrusion and security maintenance. The classical KDDCUP99 dataset has been utilized in this work for performing the experimentation with the improved algorithms. The algorithm’s detection rate and false alarm rate are compared with the experimental data before the improvement. The outcomes of proposed algorithms are analyzed in terms of various simulation parameters like average time, false alarm rate, absolute error as well as accuracy value. The results show that the improved algorithm advances the detection efficiency and accuracy using the designed detection model. The improved and tested detection model is then applied to a new intrusion detection system. After intrusion detection experiments, the experimental results show that the proposed system improves detection accuracy and reduces the false alarm rate. A significant improvement of 90.57% can be seen in detecting new attack type intrusion detection using the proposed algorithm.

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Song, Yan, Haixu Tang, Haoyu Zhang, and Qin Zhang. "Overlap detection on long, error-prone sequencing reads via smooth q-gram." Bioinformatics 36, no. 19 (April 20, 2020): 4838–45. http://dx.doi.org/10.1093/bioinformatics/btaa252.

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Abstract Motivation Third generation sequencing techniques, such as the Single Molecule Real Time technique from PacBio and the MinION technique from Oxford Nanopore, can generate long, error-prone sequencing reads which pose new challenges for fragment assembly algorithms. In this paper, we study the overlap detection problem for error-prone reads, which is the first and most critical step in the de novo fragment assembly. We observe that all the state-of-the-art methods cannot achieve an ideal accuracy for overlap detection (in terms of relatively low precision and recall) due to the high sequencing error rates, especially when the overlap lengths between reads are relatively short (e.g. <2000 bases). This limitation appears inherent to these algorithms due to their usage of q-gram-based seeds under the seed-extension framework. Results We propose smooth q-gram, a variant of q-gram that captures q-gram pairs within small edit distances and design a novel algorithm for detecting overlapping reads using smooth q-gram-based seeds. We implemented the algorithm and tested it on both PacBio and Nanopore sequencing datasets. Our benchmarking results demonstrated that our algorithm outperforms the existing q-gram-based overlap detection algorithms, especially for reads with relatively short overlapping lengths. Availability and implementation The source code of our implementation in C++ is available at https://github.com/FIGOGO/smoothq. Supplementary information Supplementary data are available at Bioinformatics online.

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Chen, Xin W., and Shimon Y. Nof. "Error Detection and Prediction Algorithms: Application in Robotics." Journal of Intelligent and Robotic Systems 48, no. 2 (January 5, 2007): 225–52. http://dx.doi.org/10.1007/s10846-006-9094-9.

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JUNG, YUNHO, SEONGJOO LEE, and JAESEOK KIM. "DESIGN AND IMPLEMENTATION OF SYMBOL DETECTOR FOR MIMO SPATIAL MULTIPLEXING SYSTEMS." Journal of Circuits, Systems and Computers 20, no. 04 (June 2011): 727–39. http://dx.doi.org/10.1142/s0218126611007578.

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In this paper, we propose an efficient symbol detection algorithm for multiple-input multiple-output spatial multiplexing (MIMO-SM) systems and present its design and implementation results. By enhancing the error performance of the first detected symbol that causes error propagation, the proposed algorithm achieves a considerable performance gain compared with the conventional sorted QR decomposition (SQRD) based detection and the ordered successive detection (OSD) algorithms. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by a simulation. In the case of a 16QAM MIMO-SM system with 4 transmit and 4 receive (4 × 4) antennas, at BER = 10-3 the proposed algorithm results in a gain improvement of about 2.5–13.5 dB over the previous algorithms. The proposed detection algorithm was designed in a hardware description language (HDL) and synthesized to gate-level circuits using 0.18 μm 1.8 V CMOS standard cell library. The results show that the proposed algorithm can be implemented without increasing the hardware costs significantly.

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Dissertations / Theses on the topic "Error detection algorithms"

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Pazaitis, Dimitrios I. "Performance improvement in adaptive signal processing algorithms." Thesis, Imperial College London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368771.

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O'Connell, Jeffrey R. "Algorithms for linkage analysis, error detection and haplotyping in pedigrees." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325622.

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Santos, Fernando Fernandes dos. "Reliability evaluation and error mitigation in pedestrian detection algorithms for embedded GPUs." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/159210.

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A confiabilidade de algoritmos para detecção de pedestres é um problema fundamental para carros auto dirigíveis ou com auxílio de direção. Métodos que utilizam algoritmos de detecção de objetos como Histograma de Gradientes Orientados (HOG - Histogram of Oriented Gradients) ou Redes Neurais de Convolução (CNN – Convolutional Neural Network) são muito populares em aplicações automotivas. Unidades de Processamento Gráfico (GPU – Graphics Processing Unit) são exploradas para executar detecção de objetos de uma maneira eficiente. Infelizmente, as arquiteturas das atuais GPUs tem se mostrado particularmente vulneráveis a erros induzidos por radiação. Este trabalho apresenta uma validação e um estudo analítico sobre a confiabilidade de duas classes de algoritmos de detecção de objetos, HOG e CNN. Esta pesquisa almeja não somente quantificar, mas também qualificar os erros produzidos por radiação em aplicações de detecção de objetos em GPUs embarcadas. Os resultados experimentais com HOG foram obtidos usando duas arquiteturas de GPU embarcadas diferentes (Tegra e AMD APU), cada uma foi exposta por aproximadamente 100 horas em um feixe de nêutrons em Los Alamos National Lab (LANL). As métricas Precision e Recall foram usadas para validar a criticalidade do erro. Uma análise final mostrou que por um lado HOG é intrinsecamente resiliente a falhas (65% a 85% dos erros na saída tiveram um pequeno impacto na detecção), do outro lado alguns erros críticos aconteceram, tais que poderiam resultar em pedestres não detectados ou paradas desnecessárias do veículo. Este trabalho também avaliou a confiabilidade de duas Redes Neurais de Convolução para detecção de Objetos:Darknet e Faster RCNN. Três arquiteturas diferentes de GPUs foram expostas em um feixe de nêutrons controlado (Kepler, Maxwell, e Pascal), com as redes detectando objetos em dois data sets, Caltech e Visual Object Classes. Através da análise das saídas corrompidas das redes neurais, foi possível distinguir entre erros toleráveis e erros críticos, ou seja, erros que poderiam impactar na detecção de objetos. Adicionalmente, extensivas injeções de falhas no nível da aplicação (GDB) e em nível arquitetural (SASSIFI) foram feitas, para identificar partes críticas do código para o HOG e as CNNs. Os resultados mostraram que não são todos os estágios da detecção de objetos que são críticos para a confiabilidade da detecção final. Graças a injeção de falhas foi possível identificar partes do HOG e da Darknet, que se protegidas, irão com uma maior probabilidade aumentar a sua confiabilidade, sem adicionar um overhead desnecessário. A estratégia de tolerância a falhas proposta para o HOG foi capaz de detectar até 70% dos erros com 12% de overhead de tempo.
Pedestrian detection reliability is a fundamental problem for autonomous or aided driving. Methods that use object detection algorithms such as Histogram of Oriented Gradients (HOG) or Convolutional Neural Networks (CNN) are today very popular in automotive applications. Embedded Graphics Processing Units (GPUs) are exploited to make object detection in a very efficient manner. Unfortunately, GPUs architecture has been shown to be particularly vulnerable to radiation-induced failures. This work presents an experimental evaluation and analytical study of the reliability of two types of object detection algorithms: HOG and CNNs. This research aim is not just to quantify but also to qualify the radiation-induced errors on object detection applications executed in embedded GPUs. HOG experimental results were obtained using two different architectures of embedded GPUs (Tegra and AMD APU), each exposed for about 100 hours to a controlled neutron beam at Los Alamos National Lab (LANL). Precision and Recall metrics are considered to evaluate the error criticality. The reported analysis shows that, while being intrinsically resilient (65% to 85% of output errors only slightly impact detection), HOG experienced some particularly critical errors that could result in undetected pedestrians or unnecessary vehicle stops. This works also evaluates the reliability of two Convolutional Neural Networks for object detection: You Only Look Once (YOLO) and Faster RCNN. Three different GPU architectures were exposed to controlled neutron beams (Kepler, Maxwell, and Pascal) detecting objects in both Caltech and Visual Object Classes data sets. By analyzing the neural network corrupted output, it is possible to distinguish between tolerable errors and critical errors, i.e., errors that could impact detection. Additionally, extensive GDB-level and architectural-level fault-injection campaigns were performed to identify HOG and YOLO critical procedures. Results show that not all stages of object detection algorithms are critical to the final classification reliability. Thanks to the fault injection analysis it is possible to identify HOG and Darknet portions that, if hardened, are more likely to increase reliability without introducing unnecessary overhead. The proposed HOG hardening strategy is able to detect up to 70% of errors with a 12% execution time overhead.

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Lee, Ho. "Algorithms to Improve the Quality of Freeway Traffic Detector Data." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345522267.

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Hua, Nan. "Space-efficient data sketching algorithms for network applications." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44899.

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Sketching techniques are widely adopted in network applications. Sketching algorithms “encode” data into succinct data structures that can later be accessed and “decoded” for various purposes, such as network measurement, accounting, anomaly detection and etc. Bloom filters and counter braids are two well-known representatives in this category. Those sketching algorithms usually need to strike a tradeoff between performance (how much information can be revealed and how fast) and cost (storage, transmission and computation). This dissertation is dedicated to the research and development of several sketching techniques including improved forms of stateful Bloom Filters, Statistical Counter Arrays and Error Estimating Codes. Bloom filter is a space-efficient randomized data structure for approximately representing a set in order to support membership queries. Bloom filter and its variants have found widespread use in many networking applications, where it is important to minimize the cost of storing and communicating network data. In this thesis, we propose a family of Bloom Filter variants augmented by rank-indexing method. We will show such augmentation can bring a significant reduction of space and also the number of memory accesses, especially when deletions of set elements from the Bloom Filter need to be supported. Exact active counter array is another important building block in many sketching algorithms, where storage cost of the array is of paramount concern. Previous approaches reduce the storage costs while either losing accuracy or supporting only passive measurements. In this thesis, we propose an exact statistics counter array architecture that can support active measurements (real-time read and write). It also leverages the aforementioned rank-indexing method and exploits statistical multiplexing to minimize the storage costs of the counter array. Error estimating coding (EEC) has recently been established as an important tool to estimate bit error rates in the transmission of packets over wireless links. In essence, the EEC problem is also a sketching problem, since the EEC codes can be viewed as a sketch of the packet sent, which is decoded by the receiver to estimate bit error rate. In this thesis, we will first investigate the asymptotic bound of error estimating coding by viewing the problem from two-party computation perspective and then investigate its coding/decoding efficiency using Fisher information analysis. Further, we develop several sketching techniques including Enhanced tug-of-war(EToW) sketch and the generalized EEC (gEEC)sketch family which can achieve around 70% reduction of sketch size with similar estimation accuracies. For all solutions proposed above, we will use theoretical tools such as information theory and communication complexity to investigate how far our proposed solutions are away from the theoretical optimal. We will show that the proposed techniques are asymptotically or empirically very close to the theoretical bounds.

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Valent, Adam. "Jednosměrná sériová komunikace laserem na větší vzdálenost." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442524.

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The subject of this thesis is the construction of one-way communication device. This device consists of the transmitter and the receiver, both of which are connected to its respective computer via USB interface. This device allows sending UTF-8 characters or files from one computer to another. Both computers are running a graphical user interface program. The core of a transmitter is a digital signal modulating laser diode. The receiver is made of photovoltaic panel with a resonance circuit and an amplifier. Communication between the electronics and the computer is driven by microcontrollers. Received messages are verified with one of multiple error detection algorithms, which can be selected by user in the utility program.

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Feng, Jingbin. "Quasi-Static Deflection Compensation Control of Flexible Manipulator." PDXScholar, 1993. https://pdxscholar.library.pdx.edu/open_access_etds/4759.

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The growing need in industrial applications of high-performance robots has led to designs of lightweight robot arms. However the light-weight robot arm introduces accuracy and vibration problems. The classical robot design and control method based on the rigid body assumption is no longer satisfactory for the light-weight manipulators. The effects of flexibility of light-weight manipulators have been an active research area in recent years. A new approach to correct the quasi-static position and orientation error of the end-effector of a manipulator with flexible links is studied in this project. In this approach, strain gages are used to monitor the elastic reactions of the flexible links due to the weight of the manipulator and the payload in real time, the errors are then compensated on-line by a control algorithm. Although this approach is designed to work for general loading conditions, only the bending deflection in a plane is investigated in detail. It is found that a minimum of two strain gages per link are needed to monitor the deflection of a robot arm subjected to bending. A mathematical model relating the deflections and strains is developed using Castigliano's theorem of least work. The parameters of the governing equations are obtained using the identification method. With the identification method, the geometric details of the robot arms and the carrying load need not be known. The deflections monitored by strain gages are fed back to the kinematic model of the manipulator to find the position and orientation of the end-effector of the manipulator. A control algorithm is developed to compensate the deflections. The inverse kinematics that includes deflections as variables is solved in closed form. If the deflections at target position are known, this inverse kinematics will generate the exact joint command for the flexible manipulator. However the deflections of the robot arms at the target position are unknown ahead of time, the current deflections at each sampling time are used to predict the deflections at target position and the joint command is modified until the required accuracy is obtained. An experiment is set up to verify the mathematical model relating the strains to the deflections. The results of the experiment show good agreement with the model. The compensation control algorithm is first simulated in a computer program. The simulation also shows good convergence. An experimental manipulator with two flexible links is built to prove this approach. The experimental results show that this compensation control improves the position accuracy of the flexible manipulator significantly. The following are the brief advantages of this approach: the deflections can be monitored without measuring the payload directly and without the detailed knowledge of link geometry~ the manipulator calibrates itself with minimum human intervention; the compensation control algorithm can be easily integrated with the existing uncompensated rigid-body algorithm~ it is inexpensive and practical for implementation to manipulators installed in workplaces.

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Xie, Yichen. "Static detection of software errors precise and scalable algorithms for automatic detection of software errors." Saarbrücken VDM, Müller, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2991792&prov=M&dok_var=1&dok_ext=htm.

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Kapfunde, Goodwell. "Near-capacity sphere decoder based detection schemes for MIMO wireless communication systems." Thesis, University of Hertfordshire, 2013. http://hdl.handle.net/2299/11350.

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The search for the closest lattice point arises in many communication problems, and is known to be NP-hard. The Maximum Likelihood (ML) Detector is the optimal detector which yields an optimal solution to this problem, but at the expense of high computational complexity. Existing near-optimal methods used to solve the problem are based on the Sphere Decoder (SD), which searches for lattice points confined in a hyper-sphere around the received point. The SD has emerged as a powerful means of finding the solution to the ML detection problem for MIMO systems. However the bottleneck lies in the determination of the initial radius. This thesis is concerned with the detection of transmitted wireless signals in Multiple-Input Multiple-Output (MIMO) digital communication systems as efficiently and effectively as possible. The main objective of this thesis is to design efficient ML detection algorithms for MIMO systems based on the depth-first search (DFS) algorithms whilst taking into account complexity and bit error rate performance requirements for advanced digital communication systems. The increased capacity and improved link reliability of MIMO systems without sacrificing bandwidth efficiency and transmit power will serve as the key motivation behind the study of MIMO detection schemes. The fundamental principles behind MIMO systems are explored in Chapter 2. A generic framework for linear and non-linear tree search based detection schemes is then presented Chapter 3. This paves way for different methods of improving the achievable performance-complexity trade-off for all SD-based detection algorithms. The suboptimal detection schemes, in particular the Minimum Mean Squared Error-Successive Interference Cancellation (MMSE-SIC), will also serve as pre-processing as well as comparison techniques whilst channel capacity approaching Low Density Parity Check (LDPC) codes will be employed to evaluate the performance of the proposed SD. Numerical and simulation results show that non-linear detection schemes yield better performance compared to linear detection schemes, however, at the expense of a slight increase in complexity. The first contribution in this thesis is the design of a near ML-achieving SD algorithm for MIMO digital communication systems that reduces the number of search operations within the sphere-constrained search space at reduced detection complexity in Chapter 4. In this design, the distance between the ML estimate and the received signal is used to control the lower and upper bound radii of the proposed SD to prevent NP-complete problems. The detection method is based on the DFS algorithm and the Successive Interference Cancellation (SIC). The SIC ensures that the effects of dominant signals are effectively removed. Simulation results presented in this thesis show that by employing pre-processing detection schemes, the complexity of the proposed SD can be significantly reduced, though at marginal performance penalty. The second contribution is the determination of the initial sphere radius in Chapter 5. The new initial radius proposed in this thesis is based on the variable parameter α which is commonly based on experience and is chosen to ensure that at least a lattice point exists inside the sphere with high probability. Using the variable parameter α, a new noise covariance matrix which incorporates the number of transmit antennas, the energy of the transmitted symbols and the channel matrix is defined. The new covariance matrix is then incorporated into the EMMSE model to generate an improved EMMSE estimate. The EMMSE radius is finally found by computing the distance between the sphere centre and the improved EMMSE estimate. This distance can be fine-tuned by varying the variable parameter α. The beauty of the proposed method is that it reduces the complexity of the preprocessing step of the EMMSE to that of the Zero-Forcing (ZF) detector without significant performance degradation of the SD, particularly at low Signal-to-Noise Ratios (SNR). More specifically, it will be shown through simulation results that using the EMMSE preprocessing step will substantially improve performance whenever the complexity of the tree search is fixed or upper bounded. The final contribution is the design of the LRAD-MMSE-SIC based SD detection scheme which introduces a trade-off between performance and increased computational complexity in Chapter 6. The Lenstra-Lenstra-Lovasz (LLL) algorithm will be utilised to orthogonalise the channel matrix H to a new near orthogonal channel matrix H ̅.The increased computational complexity introduced by the LLL algorithm will be significantly decreased by employing sorted QR decomposition of the transformed channel H ̅ into a unitary matrix and an upper triangular matrix which retains the property of the channel matrix. The SIC algorithm will ensure that the interference due to dominant signals will be minimised while the LDPC will effectively stop the propagation of errors within the entire system. Through simulations, it will be demonstrated that the proposed detector still approaches the ML performance while requiring much lower complexity compared to the conventional SD.

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Sevim, Alaettin. "Including state excitation in the fixed-interval smoothing algorithm and implementation of the maneuver detection method using error residuals." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA246336.

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Thesis (M.S. in Engineering Science)--Naval Postgraduate School, December 1990.
Thesis Advisor: Titus, Harold A. Second Reader: Burl, Jeff. "December 1990." Description based on title screen as viewed on April 2, 2010. DTIC Identifier(s): Noise processing, maneuver detection. Author(s) subject terms: Kalman filter, smoothing, noise process, maneuver detection. Includes bibliographical references (p. 98-99). Also available in print.

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Books on the topic "Error detection algorithms"

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International Conference Arithmetic, Geometry, Cryptography and Coding Theory (14th 2013 Marseille, France). Algorithmic arithmetic, geometry, and coding theory: 14th International Conference, Arithmetic, Geometry, Cryptography, and Coding Theory, June 3-7 2013, CIRM, Marseille, France. Edited by Ballet Stéphane 1971 editor, Perret, M. (Marc), 1963- editor, and Zaytsev, Alexey (Alexey I.), 1976- editor. Providence, Rhode Island: American Mathematical Society, 2015.

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John F. Kennedy Space Center., ed. Development of algorithms and error analyses for the short baseline lightning detection and ranging system. Kennedy Space Center, Fla: National Aeronautics and Space Administration, John F. Kennedy Space Center, 1998.

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John F. Kennedy Space Center., ed. Development of algorithms and error analyses for the short baseline lightning detection and ranging system. Kennedy Space Center, Fla: National Aeronautics and Space Administration, John F. Kennedy Space Center, 1998.

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United States. National Aeronautics and Space Administration., ed. Minimal time change detection algorithm for reconfigurable control system and application to aerospace. [Los Angeles, CA: University of California, 1994.

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Book chapters on the topic "Error detection algorithms"

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Chen, Dewang, and Ruijun Cheng. "Error Data Detection." In Intelligent Processing Algorithms and Applications for GPS Positioning Data of Qinghai-Tibet Railway, 87–102. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-58970-0_5.

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Lafond, Manuel, Krister M. Swenson, and Nadia El-Mabrouk. "Error Detection and Correction of Gene Trees." In Models and Algorithms for Genome Evolution, 261–85. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5298-9_12.

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Weimer, Westley, and George C. Necula. "Mining Temporal Specifications for Error Detection." In Tools and Algorithms for the Construction and Analysis of Systems, 461–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31980-1_30.

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Methods, Algebraic, and 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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Shandilya, Suyash. "Minimising Acquisition Maximising Inference—A Demonstration on Print Error Detection." In Algorithms for Intelligent Systems, 413–23. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4936-6_47.

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Fang, Wentao, Jingjing Gu, Zujia Yan, and Qiuhong Wang. "SDC Error Detection by Exploring the Importance of Instruction Features." In Wireless Algorithms, Systems, and Applications, 351–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85928-2_28.

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Holmquist, Lawrence P., and L. L. Kinney. "Concurrent error detection in sequential circuits using convolutional codes." In Applied Algebra, Algebraic Algorithms and Error-Correcting Codes, 183–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54522-0_107.

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Chicano, Francisco, Marco Ferreira, and Enrique Alba. "Comparing Metaheuristic Algorithms for Error Detection in Java Programs." In Search Based Software Engineering, 82–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23716-4_11.

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Sun, Tao, Jing Zhang, and Wenjie Zhong. "Concurrent Software Fine-Coarse-Grained Automatic Modeling Method for Algorithm Error Detection." In Algorithms and Architectures for Parallel Processing, 615–23. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38961-1_52.

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Margaria, Tiziana. "Fully automatic verification and error detection for parameterized iterative sequential circuits." In Tools and Algorithms for the Construction and Analysis of Systems, 258–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61042-1_49.

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Conference papers on the topic "Error detection algorithms"

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Pfeifer, Petr, and H. T. Vierhaus. "Iterative error correction with double/triple error detection." In 2016 Signal Processing: Algorithms, Architectures, Arrangements and Applications (SPA). IEEE, 2016. http://dx.doi.org/10.1109/spa.2016.7763579.

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Halunga, Simona, Octavian Fratu, and Dragos Vizireanu. "Error Probability Evaluation for Multiuser Detection Algorithms." In 2007 8th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services. IEEE, 2007. http://dx.doi.org/10.1109/telsks.2007.4375964.

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Nikodem, Maciej. "Error Prevention, Detection and Diffusion Algorithms for Cryptographic Hardware." In 2nd International Conference on Dependability of Computer Systems (DepCoS-RELCOMEX '07). IEEE, 2007. http://dx.doi.org/10.1109/depcos-relcomex.2007.20.

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Hanayama, Ryohei, and Kenichi Hibino. "Error estimation of phase detection algorithms and comparison of window functions." In SPIE Optical Engineering + Applications, edited by Joanna Schmit, Katherine Creath, Catherine E. Towers, and Jan Burke. SPIE, 2012. http://dx.doi.org/10.1117/12.929785.

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Anitha, Kumari A., and Maya V. Karki. "Iris recognition system with error detection and reconstruction algorithms for template security." In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2017. http://dx.doi.org/10.1109/rteict.2017.8256713.

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Joerger, Mathieu, Jason Neale, Boris Pervan, and Seebany Datta-Barua. "Measurement error models and fault-detection algorithms for multi-constellation navigation systems." In 2010 IEEE/ION Position, Location and Navigation Symposium - PLANS 2010. IEEE, 2010. http://dx.doi.org/10.1109/plans.2010.5507228.

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Karaklajic, Dusko, Junfeng Fan, and Ingrid Verbauwhede. "A systematic M safe-error detection in hardware implementations of cryptographic algorithms." In 2012 IEEE International Symposium on Hardware-Oriented Security and Trust (HOST). IEEE, 2012. http://dx.doi.org/10.1109/hst.2012.6224327.

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P., Sujith, A. P. Prathosh, A. G. Ramakrishnan, and Prasanta Kumar Ghosh. "An error correction scheme for GCI detection algorithms using pitch smoothness criterion." In Interspeech 2015. ISCA: ISCA, 2015. http://dx.doi.org/10.21437/interspeech.2015-661.

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Capponi, Stefano, and Chiazor Nwachukwu. "Data Analytics Software for Automatic Detection of Anomalies in Well Testing." In SPE Offshore Europe Conference & Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205456-ms.

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Abstract This paper will present a software that was developed to diagnose well test data. The software monitors the data, and through a series of algorithms alarms the user in case of discrepancies. This allows the user to investigate possible source of errors and correct them in real time. Several datasets from previous operations were analyzed and the basic physics governing how a certain datum depends on others were laid out. All the well test data traditionally acquired were put on a matrix, showing the dependencies between each datum and other physical properties that are available - either measured or modelled. Acceptable fluctuations in acquired data were also identified for use as tolerance limits. The software scans through the data as it is acquired and raises an alarm when the identified dependencies are broken. The software also identified which parameter is most likely causing the error. The software was built based on previous well test data and reports. Subsequently, two field trials were conducted to fine tune the algorithms and allowable data fluctuations. The process of validating the software consisted of: (1) Identifying flagged errors that should have not been flagged (dependencies set too tight); (2) identifying errors that should have been flagged and were not (dependencies set too loose); (3) improving the user interface for ease of use. The results were positive, with several improvements in the error recognition and several discrepancies flagged that would not have been caught by the naked eye. The user interface was also improved, allowing the user to clear error messages and provide input to improve the algorithm. The field trial also demonstrated that the methodology is scalable to other data acquisition plans and to more advanced analytics. The algorithms are simple, allowing the software to be implemented in all operations. More advanced algorithms are likely to depend on job specific data and parameters. Traditional data acquisition systems used during well test only present the data. Alarms trigger the user's attention only when certain defined operability limits are about to be reached. Being able to confirm that the data is cohesive during the well test prevents a loss of confidence in the results and painful post processing exercises. Moreover, given the algorithms used are based on simple physics, it is easy to deploy the software in any operation.

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DePold, Hans R., Ravi Rajamani, William H. Morrison, and Krishna R. Pattipati. "A Unified Metric for Fault Detection and Isolation in Engines." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-91095.

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In this paper we make two key contributions. First, we formalize the effectiveness of fault detection and isolation (FDI) with a metric that globally considers the following: variance in engine parameter estimate residuals under normal conditions, costs of missed detections and false alarms, costs associated with misclassification of faults, fault frequencies and fault severities. Reducing the error variance increases the signal-to-noise ratio, thereby increasing the reliability and speed of fault-detection algorithms. Minimizing missed detections has enormous implications on operational safety, while minimizing false alarms and fault misclassifications has implications on downtime, asset management, cannot duplicates, and operational costs. This metric measures the trade off between reducing data error variances, between false and missed detects, and misclassification of faults. As a second contribution, we embed this metric in a systematic data-driven diagnostic optimization process for normative decisions on input parameter selection for residual generation, FDI methods and prediction/classification fusion techniques.

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Reports on the topic "Error detection algorithms"

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Varshney, Pramod K., and Wael Hashlamoun. ALGORITHMS FOR SENSOR FUSION: Applications of Distance Measures and Probability of Error Bounds to Distributed. Detection Systems. Volume 2. Fort Belvoir, VA: Defense Technical Information Center, December 1991. http://dx.doi.org/10.21236/ada254634.

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