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Relevant bibliographies by topics / Redundant representation

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Academic literature on the topic 'Redundant representation'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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Journal articles on the topic "Redundant representation"

1

Correia, Marisol B. "A Study of Redundancy and Neutrality in Evolutionary Optimization." Evolutionary Computation 21, no. 3 (2013): 413–43. http://dx.doi.org/10.1162/evco_a_00090.

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Some authors consider that evolutionary search may be positively influenced by the use of redundant representations, whereas others note that the addition of random redundancy to a representation could be useless in optimization. Given this lack of consensus, two new families of redundant binary representations are developed in this paper. The first family is based on linear transformations and is considered non-neutral. The second family of representations is designed to implement neutrality, and is based on the mathematical formulation of error control codes. A study aimed at assessing the i

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Amaricai, Alexandru, Ovidiu Sicoe, and Oana Boncalo. "On the Redundant Representation of Partial Remainders in Radix-4 SRT Dividers." Journal of Circuits, Systems and Computers 26, no. 06 (2017): 1750097. http://dx.doi.org/10.1142/s0218126617500979.

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Most digit-recurrence algorithms for division, such as the Sweeney–Robertson–Tocher (SRT) algorithm, have been used in order to take advantage of the redundant representations of the partial remainder. This way, full carry propagate additions are avoided, obtaining significant latency improvements. Furthermore, the delay corresponding to one division iteration is independent of the size of the operands. The most frequent redundant form for the partial remainders is the carry-save (CS) representation, which uses 2 bits of representation (carry and sum bits) for each bit of the partial remainder

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Raich, Anne M., and Jamshid Ghaboussi. "Implicit Representation in Genetic Algorithms Using Redundancy." Evolutionary Computation 5, no. 3 (1997): 277–302. http://dx.doi.org/10.1162/evco.1997.5.3.277.

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A new representation combining redundancy and implicit fitness constraints is introduced that performs better than a simple genetic algorithm (GA) and a structured GA in experiments. The implicit redundant representation (IRR) consists of a string that is over-specified, allowing for sections of the string to remain inactive during function evaluation. The representation does not require the user to prespecify the number of parameters to evaluate or the location of these parameters within the string. This information is obtained implicitly by the fitness function during the GA operations. The

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Miklautz, Lukas, Dominik Mautz, Muzaffer Can Altinigneli, Christian Böhm, and Claudia Plant. "Deep Embedded Non-Redundant Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 5174–81. http://dx.doi.org/10.1609/aaai.v34i04.5961.

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Complex data types like images can be clustered in multiple valid ways. Non-redundant clustering aims at extracting those meaningful groupings by discouraging redundancy between clusterings. Unfortunately, clustering images in pixel space directly has been shown to work unsatisfactory. This has increased interest in combining the high representational power of deep learning with clustering, termed deep clustering. Algorithms of this type combine the non-linear embedding of an autoencoder with a clustering objective and optimize both simultaneously. None of these algorithms try to find multiple

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Prakash, R. Vijaya, S. S. V. N. Sarma, and M. Sheshikala. "Generating Non-redundant Multilevel Association Rules Using Min-max Exact Rules." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4568. http://dx.doi.org/10.11591/ijece.v8i6.pp4568-4576.

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Association Rule mining plays an important role in the discovery of knowledge and information. Association Rule mining discovers huge number of rules for any dataset for different support and confidence values, among this many of them are redundant, especially in the case of multi-level datasets. Mining non-redundant Association Rules in multi-level dataset is a big concern in field of Data mining. In this paper, we present a definition for redundancy and a concise representation called Reliable Exact basis for representing non-redundant Association Rules from multi-level datasets. The given n

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Brabec, Tomáš. "Speculatively Redundant Continued Logarithm Representation." IEEE Transactions on Computers 59, no. 11 (2010): 1441–54. http://dx.doi.org/10.1109/tc.2010.110.

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Huapeng Wu, M. A. Hasan, I. F. Blake, and Shuhong Gao. "Finite field multiplier using redundant representation." IEEE Transactions on Computers 51, no. 11 (2002): 1306–16. http://dx.doi.org/10.1109/tc.2002.1047755.

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Idiart, Marco, Barry Berk, and L. F. Abbott. "Reduced Representation by Neural Networks with Restricted Receptive Fields." Neural Computation 7, no. 3 (1995): 507–17. http://dx.doi.org/10.1162/neco.1995.7.3.507.

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Model neural networks can perform dimensional reductions of input data sets using correlation-based learning rules to adjust their weights. Simple Hebbian learning rules lead to an optimal reduction at the single unit level but result in highly redundant network representations. More complex rules designed to reduce or remove this redundancy can develop optimal principal component representations, but they are not very compelling from a biological perspective. Neurons in biological networks have restricted receptive fields limiting their access to the input data space. We find that, within thi

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Barik, Ranjan Kumar, Manoranjan Pradhan, and Rutuparna Panda. "Efficient Conversion Technique from Redundant Binary to NonRedundant Binary Representation." Journal of Circuits, Systems and Computers 26, no. 09 (2017): 1750135. http://dx.doi.org/10.1142/s0218126617501353.

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Redundant Binary (RB) to Two’s Complement (TC) converter offers nonredundant representation. However, the sign bit of TC representation has to be handled using nonstandard hardware blocks. The concept of Inverted encoding of negative weighted bits (IEN) eliminates the need of sign extension and offers design only using predefined hardware blocks. NonRedundant Binary (NRB) representation refers to both conventional and IEN representations. The NRB representation is also useful considering problem related to shifting in Carry Save (CS) representation of a RB number. In this paper, we have propos

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Elad, Michael. "Sparse and Redundant Representation Modeling—What Next?" IEEE Signal Processing Letters 19, no. 12 (2012): 922–28. http://dx.doi.org/10.1109/lsp.2012.2224655.

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Dissertations / Theses on the topic "Redundant representation"

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Takagi, Naofumi. "Studies on Hardware Algorithms for Arithmetic Operations with a Redundant Binary Representation." Kyoto University, 1988. http://hdl.handle.net/2433/154053.

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Muir, James. "Efficient Integer Representations for Cryptographic Operations." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1099.

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Every positive integer has a unique radix 2 representation which uses the digits {0,1}. However, if we allow digits other than 0 and 1, say {0,1,-1}, then a positive integer has many representations. Of these <i>redundant</i> representations, it is possible to choose one that has few nonzero digits. It is well known that using representations of integers with few nonzero digits allows certain algebraic operations to be done more quickly. This thesis is concerned with various representations of integers that are related to efficient implementations of algebraic operations in crypto

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高木, 直史, and Naofumi Takagi. "A hardware algorithm for modular multiplication/division." IEEE, 2005. http://hdl.handle.net/2237/5293.

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Cogswell, Michael Andrew. "Understanding Representations and Reducing their Redundancy in Deep Networks." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/78167.

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Neural networks in their modern deep learning incarnation have achieved state of the art performance on a wide variety of tasks and domains. A core intuition behind these methods is that they learn layers of features which interpolate between two domains in a series of related parts. The first part of this thesis introduces the building blocks of neural networks for computer vision. It starts with linear models then proceeds to deep multilayer perceptrons and convolutional neural networks, presenting the core details of each. However, the introduction also focuses on intuition by visualizing c

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Al-Hasani, Firas Ali Jawad. "Multiple Constant Multiplication Optimization Using Common Subexpression Elimination and Redundant Numbers." Thesis, University of Canterbury. Electrical and Computer Engineering, 2014. http://hdl.handle.net/10092/9054.

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The multiple constant multiplication (MCM) operation is a fundamental operation in digital signal processing (DSP) and digital image processing (DIP). Examples of the MCM are in finite impulse response (FIR) and infinite impulse response (IIR) filters, matrix multiplication, and transforms. The aim of this work is minimizing the complexity of the MCM operation using common subexpression elimination (CSE) technique and redundant number representations. The CSE technique searches and eliminates common digit patterns (subexpressions) among MCM coefficients. More common subexpressions can be found

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Neuhäuser, David [Verfasser], Eberhard [Akademischer Betreuer] Zehendner, Werner [Akademischer Betreuer] Erhard, and Dietmar [Akademischer Betreuer] Fey. "Design and evaluation of computer arithemetic based on carry-save and signed-digit redundant number representations / David Neuhäuser. Gutachter: Eberhard Zehendner ; Werner Erhard ; Dietmar Fey." Jena : Thüringer Universitäts- und Landesbibliothek Jena, 2012. http://d-nb.info/1024079899/34.

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Cruz, Ruiz Ana Lucia. "Low-Dimensional Control Representations for Muscle-Based Characters : Application to Overhead Throwing." Thesis, Rennes, École normale supérieure, 2016. http://www.theses.fr/2016ENSR0005/document.

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L’utilisation de personnages virtuels dans le cadre de simulations basées sur les lois de la physique trouve maintenant des applications allant de la biomécanique à l’animation. L’un des éléments incontournables de cette performance est le contrôleur de mouvement, capable de transformer les actions souhaitées en mouvements synthétisés. La conceptualisation de ces contrôleurs a profondément évolué grâce à l'apport des connaissances en biomécanique qui a conduit à l'utilisation de modèles de personnages encore plus détaillés car s'inspirant de l’appareil squelettique et surtout musculaire de l’ê

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Michelucci, Dominique. "Les représentations par les frontières : quelques constructions; difficultés rencontrées." Saint-Etienne, EMSE, 1987. http://tel.archives-ouvertes.fr/docs/00/83/03/69/PDF/1987_Michelucci_Dominique.pdf.

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La synthèse d'images et la CAO utilisent diverses modélisations des solides. Les représentations par les frontières "Boundary Representations" sont l'une d'elles. Leurs constructions se heurtent à plusieurs difficultés : l'imprécision numérique dont les conséquences néfastes ont peut être été sous-estimées, les possibles incohérences (comment être sûr qu'une représentation par frontières décrit bien un solide, au sens physique du terme?) provoquées par les imprécisions numériques et/ou la redondance des représentations par les frontières, et enfin le foisonnement des cas particuliers. Cette th

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Blanc, Alexandre. "Les métamorphoses de la garantie des créances salariales." Thesis, Paris 2, 2016. http://www.theses.fr/2016PA020012.

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En période de crise économique, la question de la garantie de paiement du salaire se pose avec acuité en cas d’insolvabilité de l’employeur. En France, cette protection est assurée par un fonds de garantie géré par l’association pour la gestion du régime de garantie des créances des salariés Depuis sa création en 1974, l’AGS a subi d’importantes mutations : initialement conçue pour pallier les insuffisances d’une protection bâtie sur un système de privilèges, elle est désormais un « amortisseur social » pour les salariés de l’entreprise en difficulté. Paradoxalement, cette évolution est égalem

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Céa, Aurélie. "L'unité économique et sociale en droit du travail." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0053/document.

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L’UES constitue un outil de recomposition du cadre de l’entreprise. Le recours à l’UES permet en effetde considérer que plusieurs entités juridiquement distinctes constituent, en droit du travail, uneentreprise unique. La reconnaissance de l’UES facilite alors la mise en oeuvre de normes déterminéespar le juge ou le législateur, parmi lesquelles figurent en premier lieu celles relatives à la représentationcollective du personnel. L’évolution de son utilisation a façonné son périmètre en un cadre d’exercicedes droits collectifs des salariés. Toutefois, si le recours à l’UES correspond à la rech

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Books on the topic "Redundant representation"

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Elad, Michael. Sparse and Redundant Representations. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7011-4.

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Elad, M. Sparse and redundant representations: From theory to applications in signal and image processing. Springer, 2010.

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Elad, Michael. Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing. Springer, 2014.

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Book chapters on the topic "Redundant representation"

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Geiselmann, Willi, and Harald Lukhaub. "Redundant Representation of Finite Fields." In Public Key Cryptography. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44586-2_25.

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Miomo, Takahiro, Koichi Yasuoka, and Masanori Kanazawa. "The Fastest Multiplier on FPGAs with Redundant Binary Representation." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44614-1_56.

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Shi, Jianglin, Changhai Liu, Rong Xu, and Tao Men. "Image Fusion Method Based on Sparse and Redundant Representation." In Proceedings of the 28th Conference of Spacecraft TT&C Technology in China. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4837-1_26.

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Szulc, Iwona, Krzysztof Stencel, and Piotr Wiśniewski. "Using Genetic Algorithms to Optimize Redundant Data." In Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58274-0_14.

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He, Yajuan, Jiaxing Yang, and Chip-Hong Chang. "Design and Evaluation of Booth-Encoded Multipliers in Redundant Binary Representation." In Embedded Systems Design with Special Arithmetic and Number Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49742-6_6.

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Tripathy, Snigdha Subhadarshinee, Ranjan Kumar Barik, and Manoranjan Pradhan. "An Improved Conversion Circuit for Redundant Binary to Conventional Binary Representation." In Communications in Computer and Information Science. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6427-2_29.

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Soper, A. J., and P. F. Robbins. "A Redundant Representation for use by Genetic Algorithms on Parameter Optimisation Problems." In Artificial Neural Nets and Genetic Algorithms. Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6492-1_44.

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Vigoriti, Fabio, Fabio Ruggiero, Vincenzo Lippiello, and Luigi Villani. "Tracking Control of Redundant Manipulators with Singularity-Free Orientation Representation and Null-Space Compliant Behaviour." In Springer Proceedings in Advanced Robotics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89327-3_2.

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Elad, Michael. "Prologue." In Sparse and Redundant Representations. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7011-4_1.

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Elad, Michael. "Image Deblurring – A Case Study." In Sparse and Redundant Representations. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7011-4_10.

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Conference papers on the topic "Redundant representation"

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Zhu, S. M., B. W. H. Ng, B. M. Fischer, and D. Abbott. "THz signal denoising via redundant representation." In 2009 34th International Conference on Infrared, Millimeter, and Terahertz Waves (IORMMW-THz 2009). IEEE, 2009. http://dx.doi.org/10.1109/icimw.2009.5325609.

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Li, Sanjiang, Zhiguo Long, Weiming Liu, Matt Duckham, and Alan Both. "On Redundant Topological Constraints (Extended Abstract)." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/714.

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Redundancy checking is an important task in AI subfields such as knowledge representation and constraint solving. This paper considers redundant topological constraints, defined in the region connection calculus RCC8. We say a constraint in a set C of RCC8 constraints is redundant if it is entailed by the rest of C. A prime subnetwork of C is a subset of C which contains no redundant constraints and has the same solution set as C. It is natural to ask how to compute such a prime subnetwork, and when it is unique. While this problem is in general intractable, we show that, if S is a subalgebra

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Zhang, Ying, Chenqiang Gao, Luxing Li, and Qiang Li. "Infrared image denoising via sparse representation over redundant dictionary." In 2012 5th International Congress on Image and Signal Processing (CISP). IEEE, 2012. http://dx.doi.org/10.1109/cisp.2012.6469823.

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Shugang Wei. "A new residue adder with redundant binary number representation." In 2008 Joint International IEEE Northeast Workshop on Circuits and Systems (NEWCAS) and TAISA Conference (NEWCAS-TAISA). IEEE, 2008. http://dx.doi.org/10.1109/newcas.2008.4606345.

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Chang*, Dekuan, Yihui Wang, and Guangzhi Zhang. "Seismic data denoising based on sparse and redundant representation." In SEG Technical Program Expanded Abstracts 2015. Society of Exploration Geophysicists, 2015. http://dx.doi.org/10.1190/segam2015-5736502.1.

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Kingston, A., B. Parrein, and F. Autrusseau. "Redundant image representation via multi-scale digital Radon projections." In 2008 15th IEEE International Conference on Image Processing - ICIP 2008. IEEE, 2008. http://dx.doi.org/10.1109/icip.2008.4712406.

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Edamatsu, Taniguchi, Nishiyama, and Kuninobu. "A 33 Mflops Floating Point Processor Using Redundant Binary Representation." In 1988 IEEE International Solid-State Circuits Conference. IEEE, 1988. http://dx.doi.org/10.1109/isscc.1988.663676.

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Tillo, Tammam, Marco Grangetto, and Gabriella Olmo. "H.264 Multiple Description Coding Based on Redundant Picture Representation." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4380006.

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Akcakaya, Mehmet, and Vahid Tarokh. "Performance Study of Various Sparse Representation Methods Using Redundant Frames." In 2007 41st Annual Conference on Information Sciences and Systems. IEEE, 2007. http://dx.doi.org/10.1109/ciss.2007.4298400.

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Kuczborski, Wojciech, Yianni Attikiouzel, and Gregory A. Crebbin. "Video rate morphological processor based on a redundant number representation." In Robotics - DL tentative, edited by Bruce G. Batchelor, Michael J. W. Chen, and Frederick M. Waltz. SPIE, 1992. http://dx.doi.org/10.1117/12.58793.

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