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Littérature scientifique sur le sujet « Local decoding »

Auteur : Grafiati

Publié le 25 mai 2024

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Articles de revues sur le sujet "Local decoding"

Jackson, Andrew, and Thomas M. Hall. "Decoding Local Field Potentials for Neural Interfaces." IEEE Transactions on Neural Systems and Rehabilitation Engineering 25, no. 10 (2017): 1705–14. http://dx.doi.org/10.1109/tnsre.2016.2612001.

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Scruby, T. R., and K. Nemoto. "Local Probabilistic Decoding of a Quantum Code." Quantum 7 (August 29, 2023): 1093. http://dx.doi.org/10.22331/q-2023-08-29-1093.

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flip is an extremely simple and maximally local classical decoder which has been used to great effect in certain classes of classical codes. When applied to quantum codes there exist constant-weight errors (such as half of a stabiliser) which are uncorrectable for this decoder, so previous studies have considered modified versions of flip, sometimes in conjunction with other decoders. We argue that this may not always be necessary, and present numerical evidence for the existence of a threshold for flip when applied to the looplike syndromes of a three-dimensional toric code on a cubic lattice. This result can be attributed to the fact that the lowest-weight uncorrectable errors for this decoder are closer (in terms of Hamming distance) to correctable errors than to other uncorrectable errors, and so they are likely to become correctable in future code cycles after transformation by additional noise. Introducing randomness into the decoder can allow it to correct these "uncorrectable" errors with finite probability, and for a decoding strategy that uses a combination of belief propagation and probabilistic flip we observe a threshold of &#x223C;5.5&#x0025; under phenomenological noise. This is comparable to the best known threshold for this code (&#x223C;7.1&#x0025;) which was achieved using belief propagation and ordered statistics decoding [Higgott and Breuckmann, 2022], a strategy with a runtime of O(n3) as opposed to the O(n) (O(1) when parallelised) runtime of our local decoder. We expect that this strategy could be generalised to work well in other low-density parity check codes, and hope that these results will prompt investigation of other previously overlooked decoders.

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Hu, Lehua. "Coding and Decoding Optimization of Remote Video Surveillance Systems." International Journal of Grid and High Performance Computing 15, no. 2 (2023): 1–15. http://dx.doi.org/10.4018/ijghpc.318405.

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In order to solve the problems of high distortion rate and low decoding efficiency of the decoded video when the current coding and decoding methods are used to encode and decode the remote video monitoring system, considering the local area network, research on the optimization method of the coding and decoding of the remote video monitoring system is proposed. The local area network is used to collect image information, to process, and to output the image information. By preprocessing the remote video monitoring system, the low frame rate remote video monitoring system is decoded in parallel. The motion information of the lost frame is estimated to realize the fast coding and decoding of the remote video monitoring system. The experimental results show that the proposed method has low distortion rate and high decoding efficiency and has high practical value.

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Islam, Mohammad S., Khondaker A. Mamun, and Hai Deng. "Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks." Computational Intelligence and Neuroscience 2017 (2017): 1–16. http://dx.doi.org/10.1155/2017/5151895.

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Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs) for robust movement decoding of Parkinson’s disease (PD) and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value) at about0.729±0.16for decoding movement from the resting state and about0.671±0.14for decoding left and right visually cued movements.

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Baranov, Pavel V., John F. Atkins, and Martina M. Yordanova. "Augmented genetic decoding: global, local and temporal alterations of decoding processes and codon meaning." Nature Reviews Genetics 16, no. 9 (2015): 517–29. http://dx.doi.org/10.1038/nrg3963.

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Adjemov, S. S., A. I. Kostogryzov, and A. O. Atakishchev. "METAGRAMMATICAL MODEL AND METHOD OF DECODING THE VIDEOGRAPHICAL INFORMATION WITH PREFIX COMPRESSION CODES." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 193 (July 2020): 24–33. http://dx.doi.org/10.14489/vkit.2020.07.pp.024-033.

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In the article, a metagrammatic model and the local-frequency decoding method are proposed to solve the problem of decoding videographic information with prefix compression codes. The metagrammatic model is presented as a five – level stochastic metagrammatics that allows us to take into account the structural and statistical features of prefix coded data and use them to improve the decoding efficiency. It is shown that only regular Chomsky grammars can be used in the proposed stochastic metagrammatics. The model uses a combined metagrammatics scheme with matching rules such as “terminal – initial symbol” (TS) and “terminal – product label” (TP). It is shown that structuring the model in the form of stochastic metagrammatics can significantly reduce the total number of products in metagrammatics and simplify its modification when solving problems of decoding promising prefix compression codes. The features of the local-frequency method of decoding videographic information with prefix compression codes focused on this metagrammatic model are considered. To implement one of the main and time-consuming procedures of this method, related to the search in local code tables and translation of uneven prefix codes, a local-private procedure for searching code words is proposed. The features of the software implementation of the proposed method are considered. The results of experimental testing of the method on the example of real arrays of non-uniform prefix codes are presented.

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Prakash, Surya S., J. Patrick Mayo, and Supratim Ray. "Decoding of attentional state using local field potentials." Current Opinion in Neurobiology 76 (October 2022): 102589. http://dx.doi.org/10.1016/j.conb.2022.102589.

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Gur, Tom, and Oded Lachish. "On the Power of Relaxed Local Decoding Algorithms." SIAM Journal on Computing 50, no. 2 (2021): 788–813. http://dx.doi.org/10.1137/19m1307834.

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Hanks, Michael, William J. Munro, and Kae Nemoto. "Decoding Quantum Error Correction Codes With Local Variation." IEEE Transactions on Quantum Engineering 1 (2020): 1–8. http://dx.doi.org/10.1109/tqe.2020.2967890.

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Thèses sur le sujet "Local decoding"

Grigorescu, Elena Ph D. Massachusetts Institute of Technology. "Local list decoding of homomorphisms." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37929.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. Includes bibliographical references (leaves 47-49). We investigate the local-list decodability of codes whose codewords are group homomorphisms. The study of such codes was intiated by Goldreich and Levin with the seminal work on decoding the Hadamard code. Many of the recent abstractions of their initial algorithm focus on Locally Decodable Codes (LDC's) over finite fields. We derive our algorithmic approach from the list decoding of the Reed-Muller code over finite fields proposed by Sudan, Trevisan and Vadhan. Given an abelian group G and a fixed abelian group H, we give combinatorial bounds on the number of homomorphisms that have agreement 6 with an oracle-access function f : G --> H. Our bounds are polynomial in , where the degree of the polynomial depends on H. Also, depends on the distance parameter of the code, namely we consider to be slightly greater than 1-minimum distance. Furthermore, we give a local-list decoding algorithm for the homomorphisms that agree on a 3 fraction of the domain with a function f, the running time of which is poly(1/e, log G). by Elena Grigorescu. S.M.

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Ross, Max. "Decoding museum gazes : a study of visitors to local museums." Thesis, Keele University, 2003. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409554.

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Grouès, Lucien. "Decoding of LDPC quantum codes." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS413.

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Afin de pouvoir réaliser des calculs utiles grâce à des ordinateurs quantiques nous devons rendre l’information quantique plus robuste contre le bruit. Une approche prometteuse repose sur l’utilisation de code quantiques LDPC, qui nécessitent d’être associés à un décodeur. Dans cette thèse nous étudions le décodage de codes quantiques LDPC, et en particulier de codes produits d’hypergraphes, par diverse décodeurs. Nous commençons par étudier un décodeur focalisé sur les performances et obtenus en combinant deux décodeurs existants, BP et SSF. Nous montrons par des simulations que ses performances sont meilleurs que celles de chacun des deux décodeurs seuls sur des codes produits d’hypergraphes aléatoires. Nous nous concentrons ensuite sur un décodeur plus simple à analyser et ayant des garanties théoriques intéressantes, en continuant l’importation du décodeur LP qu cas quantiques, travail entamé par Li et Vontobel. Nous réussissons à prouver des résultats négatifs limitant les performances asymptotiques du décodeur sur plusieurs codes quantiques LDPC, tout en obtenant de bons résultats sur des codes produits d’hypergraphes de tailles réalistes. Enfin nous étudions le décodage local de codes quantiques LDPC, et plus particulièrement nous analysons par des simulations les performances de l’implémentation la plus rapide et la plus locale de SSF To be able to perform useful computations employing quantum computers we need to make quantum information more robust against noise. One promising approach is to protect the information using quantum LDPC codes, however they are useless without a powerful decoder. In this thesis we will study the decoding of LDPC quantum codes, and in particular of hypergraph product codes with several decoders. We first study a decoder solely focused on performance obtained from the combination of two already existing decoders, BP and SSF. We show through simulations that it has improved performance on random hypergraph product codes compared to each of the decoders alone. Later we concentrate on a decoder easier to analyse which exhibits interesting theoretical guarantees by continuing the work started by Li and Vontobel of importing the LP decoder to quantum error correction. We manage to prove negative results affecting the asymptotic performance on several LDPC quantum codes, while showing that it still performs well on hypergraph product codes of realistic size. Finally we focus on local decoders for the decoding of quantum LDPC code. In particular we numerically study a parallel variant of SSF in its fastest and most local implementation

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Tanniou, Sophie Nicole Isabelle. "Decoding identities in 'Francophone' African postcolonial spaces : local novels, global narratives." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/6360/.

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My research bridges the gap between Anglophone postcolonial studies and Francophone literary studies by looking at Francophone literature from West and Equatorial Africa, which remains under-studied in France. This work answers key questions: how can this literature be interpreted beyond its current confines? How does it rethink local and global identities? What theoretical configurations can be applied to these writers to bring them into greater academic and public prominence? I propose a comprehensive analysis of this literature’s significance in the world through a comparative reading of five contemporary regional novels in their political, social and historical context. This multidirectional reading allows me to evoke what Dominic Thomas calls an ‘intercultural dynamics’ in which colonialism ‘finds itself relocated as a mechanism that proceeds from globalization’, and integrates various spatial zones in which thinking is produced. It brings forward key writers situated ‘outside of the parameters of Frenchness’ inscribed in cosmopolitan decolonizing and cultural reconstruction trends, such as Léonora Miano, a young Cameroonian author and winner of six French literary prizes; Fatou Diome, a Senegalese best-selling writer; Sénouvo Agbota Zinsou from Togo, 63 and in political exile; one contemporary writer, Kangni Alem (Togo), and one more established intellectual, Boubacar Boris Diop (Senegal).

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Carey, Michael Clay. "Telling Us What We Already Know: A Case Study Analysis of Poverty Coverage in Rural Appalachian Community News Outlets." Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1406844451.

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Shams, Bilal. "Codes LDPC non-binaire de nouvelle generation." Phd thesis, Université de Cergy Pontoise, 2010. http://tel.archives-ouvertes.fr/tel-00766409.

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Dans cette thèse, nous présentons nos travaux dans le domaine des algorithmes de décodage des codes LDPC non-binaires généralisés. Les codes LDPC binaires ont été initialement proposés par Gallager en 1963, et après quelques avancées théoriques fondamentales, ils ont été proposés dans des standards tels que DVB-S2, WI-MAX, DSL, W-LAN etc. Plus tard, les codes LDPC non-binaires (NB-LDPC) ont été pro- posés dans la littérature, et ont montré une meilleure performance pour de petites tailles de code ou lorsqu'ils sont utilisés sur des canaux non-binaires. Cependant, les avan- tages de l'utilisation de codes NB-LDPC impliquent une augmentation importante de la complexité de décodage. Pour un code défini dans un corps de Galois GF (q), la complexité est d'ordre O (q2). De même, la mémoire requise pour le stockage des messages est d'ordre O (q). Ainsi, l'implémentation d'un décodeur LDPC défini sur un corps de Galois pour q > 64 devient impossible dans la pratique. L'objectif prin- cipal de cette thèse est de développer des algorithmes avec une bonne performance et complexité réduite de sorte qu'ils deviennent implémentables. Pour une performance de décodage optimisée, non seulement l'algorithme est important, mais également la structure du code joue un rôle clé. Avec cet objectif à l'esprit, une nouvelle famille de codes appelés " cluster-NB-LDPC codes " a été élaborée ainsi que des améliorations spécifiques du décodeur non-binaire pour ces codes. Le résultat principal est que nous avons pu proposer des décodeurs pour les codes cluster-NB-LDPC avec une complex- ité réduite par rapport aux décodeurs classiques pour les codes NB-LDPC définis sur les corps de Galois, sans aucune perte de performance dans la capacité de correction vi Résumé d'erreur. Dans la première partie de la thèse, nous avons modifié l'algorithme EMS pour les cluster-codes. La généralisation directe de l'algorithme EMS aux codes cluster-NB- LDPC n'est pas réaliste . Il y a une perte de performance et une augmentation de la complexité. Par conséquent, nous proposons quelques modifications dans la procé- dure, qui non seulement améliore considérablement les performances de décodage, mais diminue également la complexité. Au niveau des noeuds de parité, cet algo- rithme conserve les mêmes limites sur le nombre d'opérations que l'algorithme EMS pour GF (q)-codes, O (nmlognm) avec nm << q. Nous proposons ensuite une autre méthode, basée sur la diversité des codes cluster, afin d'améliorer les performances de l'algorithme EMS pour les codes cluster-LDPC. Il contribue également à réduire la complexité globale du décodeur. Finalement, nous comparons les performances de décodage en utilisant cette méthode et analysons l'effet sur la complexité de décodage. Dans la dernière partie du chapitre, nous proposons une nouvelle direction pour le décodage des codes LDPC. Elle est basée sur la création des listes des mots de code qui correspondent à des noeuds de parité. Les listes sont construite de manière récur- sive dans une structure en arbre, ce qui en fait un bon candidat pour l'implémentation matérielle. Il s'agit d'une méthode nouvelle et doit encore être améliorée mais à pre- miére vue nous avons obtenu de bons résultats avec un nombre réduit d'operations.

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Hardmeier, Christian. "Discourse in Statistical Machine Translation." Doctoral thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-223798.

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This thesis addresses the technical and linguistic aspects of discourse-level processing in phrase-based statistical machine translation (SMT). Connected texts can have complex text-level linguistic dependencies across sentences that must be preserved in translation. However, the models and algorithms of SMT are pervaded by locality assumptions. In a standard SMT setup, no model has more complex dependencies than an n-gram model. The popular stack decoding algorithm exploits this fact to implement efficient search with a dynamic programming technique. This is a serious technical obstacle to discourse-level modelling in SMT. From a technical viewpoint, the main contribution of our work is the development of a document-level decoder based on stochastic local search that translates a complete document as a single unit. The decoder starts with an initial translation of the document, created randomly or by running a stack decoder, and refines it with a sequence of elementary operations. After each step, the current translation is scored by a set of feature models with access to the full document context and its translation. We demonstrate the viability of this decoding approach for different document-level models. From a linguistic viewpoint, we focus on the problem of translating pronominal anaphora. After investigating the properties and challenges of the pronoun translation task both theoretically and by studying corpus data, a neural network model for cross-lingual pronoun prediction is presented. This network jointly performs anaphora resolution and pronoun prediction and is trained on bilingual corpus data only, with no need for manual coreference annotations. The network is then integrated as a feature model in the document-level SMT decoder and tested in an English–French SMT system. We show that the pronoun prediction network model more adequately represents discourse-level dependencies for less frequent pronouns than a simpler maximum entropy baseline with separate coreference resolution. By creating a framework for experimenting with discourse-level features in SMT, this work contributes to a long-term perspective that strives for more thorough modelling of complex linguistic phenomena in translation. Our results on pronoun translation shed new light on a challenging, but essential problem in machine translation that is as yet unsolved.

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Marie, Benjamin. "Exploitation d’informations riches pour guider la traduction automatique statistique." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS066/document.

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S'il est indéniable que de nos jours la traduction automatique (TA) facilite la communication entre langues, et plus encore depuis les récents progrès des systèmes de TA statistiques, ses résultats sont encore loin du niveau de qualité des traductions obtenues avec des traducteurs humains.Ce constat résulte en partie du mode de fonctionnement d'un système de TA statistique, très contraint sur la nature des modèles qu'il peut utiliser pour construire et évaluer de nombreuses hypothèses de traduction partielles avant de parvenir à une hypothèse de traduction complète. Il existe cependant des types de modèles, que nous qualifions de « complexes », qui sont appris à partir d'informations riches. Si un enjeu pour les développeurs de systèmes de TA consiste à les intégrer lors de la construction initiale des hypothèses de traduction, cela n'est pas toujours possible, car elles peuvent notamment nécessiter des hypothèses complètes ou impliquer un coût de calcul très important. En conséquence, de tels modèles complexes sont typiquement uniquement utilisés en TA pour effectuer le reclassement de listes de meilleures hypothèses complètes. Bien que ceci permette dans les faits de tirer profit d'une meilleure modélisation de certains aspects des traductions, cette approche reste par nature limitée : en effet, les listes d'hypothèses reclassées ne représentent qu'une infime partie de l'espace de recherche du décodeur, contiennent des hypothèses peu diversifiées, et ont été obtenues à l'aide de modèles dont la nature peut être très différente des modèles complexes utilisés en reclassement.Nous formulons donc l'hypothèse que de telles listes d'hypothèses de traduction sont mal adaptées afin de faire s'exprimer au mieux les modèles complexes utilisés. Les travaux que nous présentons dans cette thèse ont pour objectif de permettre une meilleure exploitation d'informations riches pour l'amélioration des traductions obtenues à l'aide de systèmes de TA statistique.Notre première contribution s'articule autour d'un système de réécriture guidé par des informations riches. Des réécritures successives, appliquées aux meilleures hypothèses de traduction obtenues avec un système de reclassement ayant accès aux mêmes informations riches, permettent à notre système d'améliorer la qualité de la traduction.L'originalité de notre seconde contribution consiste à faire une construction de listes d'hypothèses par passes multiples qui exploitent des informations dérivées de l'évaluation des hypothèses de traduction produites antérieurement à l'aide de notre ensemble d'informations riches. Notre système produit ainsi des listes d'hypothèses plus diversifiées et de meilleure qualité, qui s'avèrent donc plus intéressantes pour un reclassement fondé sur des informations riches. De surcroît, notre système de réécriture précédent permet d'améliorer les hypothèses produites par cette deuxième approche à passes multiples.Notre troisième contribution repose sur la simulation d'un type d'information idéalisé parfait qui permet de déterminer quelles parties d'une hypothèse de traduction sont correctes. Cette idéalisation nous permet d'apporter une indication de la meilleure performance atteignable avec les approches introduites précédemment si les informations riches disponibles décrivaient parfaitement ce qui constitue une bonne traduction. Cette approche est en outre présentée sous la forme d'une traduction interactive, baptisée « pré-post-édition », qui serait réduite à sa forme la plus simple : un système de TA statistique produit sa meilleure hypothèse de traduction, puis un humain apporte la connaissance des parties qui sont correctes, et cette information est exploitée au cours d'une nouvelle recherche pour identifier une meilleure traduction Although communication between languages has without question been made easier thanks to Machine Translation (MT), especially given the recent advances in statistical MT systems, the quality of the translations produced by MT systems is still well below the translation quality that can be obtained through human translation. This gap is partly due to the way in which statistical MT systems operate; the types of models that can be used are limited because of the need to construct and evaluate a great number of partial hypotheses to produce a complete translation hypothesis. While more “complex” models learnt from richer information do exist, in practice, their integration into the system is not always possible, would necessitate a complete hypothesis to be computed or would be too computationally expensive. Such features are therefore typically used in a reranking step applied to the list of the best complete hypotheses produced by the MT system.Using these features in a reranking framework does often provide a better modelization of certain aspects of the translation. However, this approach is inherently limited: reranked hypothesis lists represent only a small portion of the decoder's search space, tend to contain hypotheses that vary little between each other and which were obtained with features that may be very different from the complex features to be used during reranking.In this work, we put forward the hypothesis that such translation hypothesis lists are poorly adapted for exploiting the full potential of complex features. The aim of this thesis is to establish new and better methods of exploiting such features to improve translations produced by statistical MT systems.Our first contribution is a rewriting system guided by complex features. Sequences of rewriting operations, applied to hypotheses obtained by a reranking framework that uses the same features, allow us to obtain a substantial improvement in translation quality.The originality of our second contribution lies in the construction of hypothesis lists with a multi-pass decoding that exploits information derived from the evaluation of previously translated hypotheses, using a set of complex features. Our system is therefore capable of producing more diverse hypothesis lists, which are globally of a better quality and which are better adapted to a reranking step with complex features. What is more, our forementioned rewriting system enables us to further improve the hypotheses produced with our multi-pass decoding approach.Our third contribution is based on the simulation of an ideal information type, designed to perfectly identify the correct fragments of a translation hypothesis. This perfect information gives us an indication of the best attainable performance with the systems described in our first two contributions, in the case where the complex features are able to modelize the translation perfectly. Through this approach, we also introduce a novel form of interactive translation, coined "pre-post-editing", under a very simplified form: a statistical MT system produces its best translation hypothesis, then a human indicates which fragments of the hypothesis are correct, and this new information is then used during a new decoding pass to find a new best translation

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Patthak, Anindya Chandra 1977. "Error correcting codes: local testing, list decoding, and applications." Thesis, 2007. http://hdl.handle.net/2152/3626.

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Tadipatri, Vijay Aditya. "Developing robust movement decoders for local field potentials." Thesis, 2015. http://hdl.handle.net/2152/31016.

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Brain Computer Interfaces (BCI) are devices that translate acquired neural signals to command and control signals. Applications of BCI include neural rehabilitation and neural prosthesis (thought controlled wheelchair, thought controlled speller etc.) to aid patients with disabilities and to augment human computer interaction. A successful practical BCI requires a faithful acquisition modality to record high quality neural signals; a signal processing system to construct appropriate features from these signals; and an algorithm to translate these features to appropriate outputs. Intracortical recordings like local field potentials provide reliable high SNR signals over long periods and suit BCI applications well. However, the non-stationarity of neural signals poses a challenge in robust decoding of subject behavior. Most BCI research focuses either on developing daily re-calibrated decoders that require exhaustive training sessions; or on providing cross-validation results. Such results ignore the variation of signal characteristics over different sessions and provide an optimistic estimate of BCI performance. Specifically, traditional BCI algorithms fail to perform at the same level on chronological data recordings. Neural signals are susceptible to variations in signal characteristics due to changes in subject behavior and learning, and variability in electrode characteristics due to tissue interactions. While training day-specific BCI overcomes signal variability, BCI re-training causes user frustration and exhaustion. This dissertation presents contributions to solve these challenges in BCI research. Specifically, we developed decoders trained on a single recording session and applied them on subsequently recorded sessions. This strategy evaluates BCI in a practical scenario with a potential to alleviate BCI user frustration without compromising performance. The initial part of the dissertation investigates extracting features that remain robust to changes in neural signal over several days of recordings. It presents a qualitative feature extraction technique based on ranking the instantaneous power of multichannel data. These qualitative features remain robust to outliers and changes in the baseline of neural recordings, while extracting discriminative information. These features form the foundation in developing robust decoders. Next, this dissertation presents a novel algorithm based on the hypothesis that multiple neural spatial patterns describe the variation in behavior. The presented algorithm outperforms the traditional methods in decoding over chronological recordings. Adapting such a decoder over multiple recording sessions (over 6 weeks) provided > 90% accuracy in decoding eight movement directions. In comparison, performance of traditional algorithms like Common Spatial Patterns deteriorates to 16% over the same time. Over time, adaptation reinforces some spatial patterns while diminishing others. Characterizing these spatial patterns reduces model complexity without user input, while retaining the same accuracy levels. Lastly, this dissertation provides an algorithm that overcomes the variation in recording quality. Chronic electrode implantation causes changes in signal-to-noise ratio (SNR) of neural signals. Thus, some signals and their corresponding features available during training become unavailable during testing and vice-versa. The proposed algorithm uses prior knowledge on spatial pattern evolution to estimate unknown neural features. This algorithm overcomes SNR variations and provides up to 93% decoding of eight movement directions over 6 weeks. Since model training requires only one session, this strategy reduces user frustration. In a practical closed-loop BCI, the user learns to produce stable spatial patterns, which improves performance of the proposed algorithms. text

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Livres sur le sujet "Local decoding"

Decoding America's ancient indian languages. Anasazi Publishing Group, 2007.

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Rowedder, Simon. Cross-Border Traders in Northern Laos. Amsterdam University Press, 2022. http://dx.doi.org/10.5117/9789463722360.

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Northern Laos has become a prominent spot in large-scale, top-down mappings and studies of neoliberal globalisation and infrastructural development linking Thailand and China, and markets further beyond. Yet in the common narrative, in which Laos appears as a weak victim helplessly exposed to its larger neighbours, attention is seldom paid to local voices. This book fills this gap. Building on long-term multi-sited fieldwork, it accompanies northern Lao cross-border traders closely in their transnational worlds of mobilities, social relations, economic experimentation and aspiration. Cross-Border Traders in Northern Laos: Mastering Smallness demonstrates that these traders’ indispensable but often invisible role in the everyday workings of the China-Laos-Thailand borderland economy relies on their rhetoric and practices of ‘smallness’—of framing their transnational trade activities in a self-deprecating manner and stressing their economic inferiority. Decoding their discursive surface of insignificance, this ethnography of ‘smallness’ foregrounds remarkable transnational social and economic skills that are mostly invisible in Sino-Southeast Asian borderland scholarship.

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Sacred Land: Decoding the Hidden History of Britain. Little, Brown Book Group Limited, 2012.

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Palmer, Martin. Sacred Land: Decoding Britain's Extraordinary Past Through Its Towns, Villages and Countryside. Little, Brown Book Group Limited, 2012.

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Yaari, Nurit. Israeli Theatre. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198746676.003.0012.

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This chapter reviews the state of Israeli theatre today, seventy-two years since the production of Racine’s Phaedra at Habima Theatre, and sums up its notable achievements, and the myriad forms, styles, artists, and institutions that together provide fertile ground for Israeli theatre’s encounters with classical drama. An overview of the seventy-two years of reception of Greek tragedy in Israeli theatre (1945–2017) demonstrates clearly that the most important development appears to be that local theatre makers have relinquished previous preconceived ideas about classical Greek drama and performance and of Aristotle’s theatrical doctrine, in favour of personal reading, study, research, and decoding of the classical works. It also presents the young and talented artists that are bringing the results of their studies and experimentations to the translation, writing, directing, and acting of classical drama to the Israeli stage, and using that drama to deliver innovative and challenging productions for today’s audiences.

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Chapitres de livres sur le sujet "Local decoding"

Grigorescu, Elena, Swastik Kopparty, and Madhu Sudan. "Local Decoding and Testing for Homomorphisms." In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11830924_35.

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Hatami, Pooya, and Madhur Tulsiani. "Approximate Local Decoding of Cubic Reed-Muller Codes Beyond the List Decoding Radius." In Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2018. http://dx.doi.org/10.1137/1.9781611975031.43.

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Gur, Tom, and Oded Lachish. "On the Power of Relaxed Local Decoding Algorithms." In Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2020. http://dx.doi.org/10.1137/1.9781611975994.83.

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Kuditchar, Nene-Lomotey. "Decoding the Paradox of Decentralization with Centralized Characteristics in Democratic Ghana." In Democratic Decentralization, Local Governance and Sustainable Development. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12378-8_3.

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Mollas, Ioannis, Nikolaos Bassiliades, and Grigorios Tsoumakas. "LioNets: Local Interpretation of Neural Networks Through Penultimate Layer Decoding." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43823-4_23.

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Watanabe, Osamu, Takeshi Sawai, and Hayato Takahashi. "Analysis of a Randomized Local Search Algorithm for LDPCC Decoding Problem." In Stochastic Algorithms: Foundations and Applications. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39816-5_5.

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Hong, Zhang, and Wu Ping. "Image Classification with Local Linear Decoding and Global Multi-feature Fusion." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24078-7_44.

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Kasami, Tadao, Hitoshi Tokushige, and Yuichi Kaji. "Sufficient Conditions on Most Likely Local Sub-codewords in Recursive Maximum Likelihood Decoding Algorithms." In Applied Algebra, Algebraic Algorithms and Error-Correcting Codes. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45624-4_35.

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van Breugel, Maria Elize, and Fred van Leeuwen. "Epi-Decoder: Decoding the Local of a Genomic Locus by Massive Combined with DNA-Barcode Sequencing." In Methods in Molecular Biology. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2140-0_8.

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Zhang, Shuai, Juan F. Quinonez-Beltran, Jialin Lai, et al. "Expressive Language Proficiency and Decoding Development in Local Languages and Portuguese in Mozambique: Evidence from Nampula and Zambézia." In Literacy Studies. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-26250-0_23.

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Actes de conférences sur le sujet "Local decoding"

Rachkidy, Nancy El, Alexre Guitton, and Megumi Kaneko. "Decoding Superposed LoRa Signals." In 2018 IEEE 43rd Conference on Local Computer Networks (LCN). IEEE, 2018. http://dx.doi.org/10.1109/lcn.2018.8638253.

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Zhu, Ziyuan, Wei Wu, and Paul H. Siegel. "Polar Codes with Local-Global Decoding." In 2022 56th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2022. http://dx.doi.org/10.1109/ieeeconf56349.2022.10051996.

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Lindberg, Eric W., Lee E. Miller, Emily R. Oby, and Marc W. Slutzky. "Decoding muscle activity with local field potentials." In 5th International IEEE/EMBS Conference on Neural Engineering (NER 2011). IEEE, 2011. http://dx.doi.org/10.1109/ner.2011.5910541.

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Dingel, Janis, Nikhil Singh, and Olgica Milenkovic. "Inferring algebraic gene networks using local decoding." In 2008 IEEE International Conference on Bioinformatics and Biomeidcine Workshops, BIBMW. IEEE, 2008. http://dx.doi.org/10.1109/bibmw.2008.4686224.

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Jensen, Arne S. "Decoding of stereo images by local correlation." In SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, edited by Robert A. Melter, Angela Y. Wu, Fred L. Bookstein, and William D. K. Green. SPIE, 1995. http://dx.doi.org/10.1117/12.216411.

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Ram, Eshed, and Yuval Cassuto. "LDPC Codes with Local and Global Decoding." In 2018 IEEE International Symposium on Information Theory (ISIT). IEEE, 2018. http://dx.doi.org/10.1109/isit.2018.8437736.

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Vatedka, Shashank, and Aslan Tchamkerten. "Local Decoding and Update of Compressed Data." In 2019 IEEE International Symposium on Information Theory (ISIT). IEEE, 2019. http://dx.doi.org/10.1109/isit.2019.8849634.

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Zhou, Wangchunshu, Tao Ge, and Ke Xu. "Pseudo-Bidirectional Decoding for Local Sequence Transduction." In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.findings-emnlp.136.

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Adegbite, S. A., S. G. Mcmeekin, and B. G. Stewart. "Improved PCFICH decoding in LTE systems." In 2015 IEEE International Workshop on Local and Metropolitan Area Networks (LANMAN). IEEE, 2015. http://dx.doi.org/10.1109/lanman.2015.7114739.

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Ryu, Junhee, Kyungtae Kang, Yongwoo Cho, Joonho Lee, and Heonshik Shin. "Energy Characterization of Reed-Solomon Decoding in 3G Broadcasting." In 2006 31st IEEE Conference on Local Computer Networks. IEEE, 2006. http://dx.doi.org/10.1109/lcn.2006.322043.

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