Relevant bibliographies by topics / LP decoder

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'LP decoder'

Author: Grafiati
Published: 25 May 2024

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Journal articles on the topic "LP decoder"

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Dimakis, Alexandros G., Amin A. Gohari, and Martin J. Wainwright. "Guessing Facets: Polytope Structure and Improved LP Decoder." IEEE Transactions on Information Theory 55, no. 8 (August 2009): 3479–87. http://dx.doi.org/10.1109/tit.2009.2023735.

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Cao, Jiaping, Jichao Li, and Jiang Jiang. "Link Prediction for Temporal Heterogeneous Networks Based on the Information Lifecycle." Mathematics 11, no. 16 (August 16, 2023): 3541. http://dx.doi.org/10.3390/math11163541.

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Link prediction for temporal heterogeneous networks is an important task in the field of network science, and it has a wide range of real-world applications. Traditional link prediction methods are mainly based on static homogeneous networks, which do not distinguish between different types of nodes in the real world and do not account for network structure evolution over time. To address these issues, in this paper, we study the link prediction problem in temporal heterogeneous networks and propose a link prediction method for temporal heterogeneous networks (LP-THN) based on the information lifecycle, which is an end-to-end encoder–decoder structure. The information lifecycle accounts for the active, decay and stable states of edges. Specifically, we first introduce the meta-path augmented residual information matrix to preserve the structure evolution mechanism and semantics in HINs, using it as input to the encoder to obtain a low-dimensional embedding representation of the nodes. Finally, the link prediction problem is considered a binary classification problem, and the decoder is utilized for link prediction. Our prediction process accounts for both network structure and semantic changes using meta-path augmented residual information matrix perturbations. Our experiments demonstrate that LP-THN outperforms other baselines in both prediction effectiveness and prediction efficiency.
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Wang, Zhuo, Alan A. Stocker, and Daniel D. Lee. "Efficient Neural Codes That Minimize Lp Reconstruction Error." Neural Computation 28, no. 12 (December 2016): 2656–86. http://dx.doi.org/10.1162/neco_a_00900.

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The efficient coding hypothesis assumes that biological sensory systems use neural codes that are optimized to best possibly represent the stimuli that occur in their environment. Most common models use information–theoretic measures, whereas alternative formulations propose incorporating downstream decoding performance. Here we provide a systematic evaluation of different optimality criteria using a parametric formulation of the efficient coding problem based on the [Formula: see text] reconstruction error of the maximum likelihood decoder. This parametric family includes both the information maximization criterion and squared decoding error as special cases. We analytically derived the optimal tuning curve of a single neuron encoding a one-dimensional stimulus with an arbitrary input distribution. We show how the result can be generalized to a class of neural populations by introducing the concept of a meta–tuning curve. The predictions of our framework are tested against previously measured characteristics of some early visual systems found in biology. We find solutions that correspond to low values of [Formula: see text], suggesting that across different animal models, neural representations in the early visual pathways optimize similar criteria about natural stimuli that are relatively close to the information maximization criterion.
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Bakheit, Ahmed H., and Hamad M. Alkahtani. "Integrated Structural, Functional, and ADMET Analysis of 2-Methoxy-4,6-Diphenylnicotinonitrile: The Convergence of X-ray Diffraction, Molecular Docking, Dynamic Simulations, and Advanced Computational Insights." Molecules 28, no. 19 (September 28, 2023): 6859. http://dx.doi.org/10.3390/molecules28196859.

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This study systematically investigates the molecular structure and electronic properties of 2-methoxy-4,6-diphenylnicotinonitrile, employing X-ray diffraction (XRD) and sophisticated computational methodologies. XRD findings validate the compound’s orthorhombic crystallization in the P21212 space group, composed of a pyridine core flanked by two phenyl rings. Utilizing the three-dimensional Hirshfeld surface, the research decodes the molecule’s spatial attributes, further supported by exhaustive statistical assessments. Key interactions, such as π–π stacking and H···X contacts, are spotlighted, underscoring their role in the crystal’s inherent stability and characteristics. Energy framework computations and density functional theory (DFT) analyses elucidate the prevailing forces in the crystal and reveal geometric optimization facets and molecular reactivity descriptors. Emphasis is given to the exploration of frontier molecular orbitals (FMOs), aromaticity, and π–π stacking capacities. The research culminates in distinguishing electron density distributions, aromatic nuances, and potential reactivity hotspots, providing a holistic view of the compound’s structural and electronic landscape. Concurrently, molecular docking investigates its interaction with the lipoprotein-associated phospholipase A2 protein. Notably, the compound showcases significant interactions with the protein’s active site. Molecular dynamics simulations reveal the compound’s influence on protein stability and flexibility. Although the molecule exhibits strong inhibitory potential against Lp-PLA2, its drug development prospects face challenges related to solubility and interactions with drug transport proteins.
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Moly, Alexandre, Alexandre Aksenov, Félix Martel, and Tetiana Aksenova. "Online adaptive group-wise sparse Penalized Recursive Exponentially Weighted N-way Partial Least Square for epidural intracranial BCI." Frontiers in Human Neuroscience 17 (March 6, 2023). http://dx.doi.org/10.3389/fnhum.2023.1075666.

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IntroductionMotor Brain–Computer Interfaces (BCIs) create new communication pathways between the brain and external effectors for patients with severe motor impairments. Control of complex effectors such as robotic arms or exoskeletons is generally based on the real-time decoding of high-resolution neural signals. However, high-dimensional and noisy brain signals pose challenges, such as limitations in the generalization ability of the decoding model and increased computational demands.MethodsThe use of sparse decoders may offer a way to address these challenges. A sparsity-promoting penalization is a common approach to obtaining a sparse solution. BCI features are naturally structured and grouped according to spatial (electrodes), frequency, and temporal dimensions. Applying group-wise sparsity, where the coefficients of a group are set to zero simultaneously, has the potential to decrease computational time and memory usage, as well as simplify data transfer. Additionally, online closed-loop decoder adaptation (CLDA) is known to be an efficient procedure for BCI decoder training, taking into account neuronal feedback. In this study, we propose a new algorithm for online closed-loop training of group-wise sparse multilinear decoders using Lp-Penalized Recursive Exponentially Weighted N-way Partial Least Square (PREW-NPLS). Three types of sparsity-promoting penalization were explored using Lpwith p = 0., 0.5, and 1.ResultsThe algorithms were tested offline in a pseudo-online manner for features grouped by spatial dimension. A comparison study was conducted using an epidural ECoG dataset recorded from a tetraplegic individual during long-term BCI experiments for controlling a virtual avatar (left/right-hand 3D translation). Novel algorithms showed comparable or better decoding performance than conventional REW-NPLS, which was achieved with sparse models. The proposed algorithms are compatible with real-time CLDA.DiscussionThe proposed algorithm demonstrated good performance while drastically reducing the computational load and the memory consumption. However, the current study is limited to offline computation on data recorded with a single patient, with penalization restricted to the spatial domain only.
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Yang, Zhijian, Peng Zhang, Xiaofeng Chen, Zhongzhu Hong, Jianwei Gong, Xiangyu Ou, Qinxia Wu, et al. "High‐confidentiality X‐ray imaging encryption using prolonged imperceptible radioluminescence memory scintillators." Advanced Materials, November 11, 2023. http://dx.doi.org/10.1002/adma.202309413.

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AbstractX‐ray imaging plays an increasingly crucial role in clinical radiography, industrial inspection and military applications. However, current X‐ray imaging technologies have difficulty in protecting against information leakage caused by brute force attacks via trial‐and‐error. Here we report high‐confidentiality X‐ray imaging encryption by fabricating ultralong radioluminescence memory films composed of lanthanide‐activated nanoscintillators (NaLuF4: Gd3+ or Ce3+) with imperceptible purely‐ultraviolet (UV) emission. Mechanistic investigations unveil that ultralong X‐ray memory is attributed to the long‐lived trapping of thermalized charge carriers within Frenkel defect states and subsequent slow release in the form of imperceptible radioluminescence. The encrypted X‐ray imaging can be securely stored in the memory film for more than 7 days and optically decoded by a layer of perovskite nanocrystal film. Importantly, our encryption strategy can protect X‐ray imaging information against brute force trial‐and‐error attacks through the perception of lifetime change in the persistent radioluminescence. We further demonstrate that the as‐fabricated flexible memory film enables to achieving of three‐dimensional X‐ray imaging encryption of curved objects with a high spatial resolution of 20 lp/mm and excellent recyclability. This study provides valuable insights into the fundamental understanding of X‐ray‐to‐UV conversion in nanocrystal lattices and opens up a new avenue toward the development of high‐confidentiality, three‐dimensional X‐ray imaging encryption technologies.This article is protected by copyright. All rights reserved
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Dissertations / Theses on the topic "LP decoder"

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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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Book chapters on the topic "LP decoder"

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Yang, Liu, Boyu Wang, Jack C. P. Cheng, Peipei Liu, and Hoon Sohn. "Real-Time Geometry Assessment Using Laser Line Scanner During Laser Powder Directed Energy Deposition Additive Manufacturing of SS316L Component with Sharp Feature." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality, 965–76. Florence: Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.97.

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Directed energy deposition (DED) is a major metal additive manufacturing (AM) technology that is increasingly used in many industries due to its ability to manufacture complex components of arbitrary shapes and sizes. However, a lack of timely geometry assessment and the consequent geometry control hinders the development of DED towards zero defect manufacturing. In this study, a real-time geometry assessment methodology is developed for laser pow-der directed energy deposition (LP-DED). A geometry assessment system is developed using a laser line scanner capable of inspecting the melt pool area, the just solidified area, as well as layer-wise inspection. An image processing method with an encoder-decoder based profile completion network was developed to obtain accurate track profile in images from real-time inspection. Experiments have been conducted to validate the proposed methodology by depositing multi-layer X-shape objects
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Yang, Liu, Boyu Wang, Jack C. P. Cheng, Peipei Liu, and Hoon Sohn. "Real-Time Geometry Assessment Using Laser Line Scanner During Laser Powder Directed Energy Deposition Additive Manufacturing of SS316L Component with Sharp Feature." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality, 965–76. Florence: Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.97.

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Directed energy deposition (DED) is a major metal additive manufacturing (AM) technology that is increasingly used in many industries due to its ability to manufacture complex components of arbitrary shapes and sizes. However, a lack of timely geometry assessment and the consequent geometry control hinders the development of DED towards zero defect manufacturing. In this study, a real-time geometry assessment methodology is developed for laser pow-der directed energy deposition (LP-DED). A geometry assessment system is developed using a laser line scanner capable of inspecting the melt pool area, the just solidified area, as well as layer-wise inspection. An image processing method with an encoder-decoder based profile completion network was developed to obtain accurate track profile in images from real-time inspection. Experiments have been conducted to validate the proposed methodology by depositing multi-layer X-shape objects
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Conference papers on the topic "LP decoder"

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Dimakis, Alexandros, and Martin Wainwright. "Guessing Facets: Polytope Structure and Improved LP Decoder." In 2006 IEEE International Symposium on Information Theory. IEEE, 2006. http://dx.doi.org/10.1109/isit.2006.262070.

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Liu, Xishuo, Stark C. Draper, and Benjamin Recht. "The l1 penalized decoder and its reweighted LP." In 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2012. http://dx.doi.org/10.1109/allerton.2012.6483408.

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Motozuka, Hiroyuki, Naoya Yosoku, Takenori Sakamoto, Takayuki Tsukizawa, Naganori Shirakata, and Koji Takinami. "A 6.16Gb/s 4.7pJ/bit/iteration LDPC decoder for IEEE 802.11ad standard in 40nm LP-CMOS." In 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2015. http://dx.doi.org/10.1109/globalsip.2015.7418406.

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Heidarpour, M. R., M. Modarres-Hashemi, M. Khosravifard, and T. A. Gulliver. "Improving the Performance of LP Decoders for Cyclic Codes." In ICC 2009 - 2009 IEEE International Conference on Communications. IEEE, 2009. http://dx.doi.org/10.1109/icc.2009.5305944.

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