Academic literature on the topic 'Gray encoding'
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Journal articles on the topic "Gray encoding"
Rowe, Jonathan, Darrell Whitley, Laura Barbulescu, and Jean-Paul Watson. "Properties of Gray and Binary Representations." Evolutionary Computation 12, no. 1 (March 2004): 47–76. http://dx.doi.org/10.1162/evco.2004.12.1.47.
Full textZhang, Ting, and Steve Blair. "Gray Level Image Encoding in Plasmonic Metasurfaces." Plasmonics 15, no. 5 (March 27, 2020): 1305–11. http://dx.doi.org/10.1007/s11468-020-01151-5.
Full textNaseri, Mosayeb, Mona Abdolmaleky, Fariborz Parandin, Negin Fatahi, Ahmed Farouk, and Reza Nazari. "A New Quantum Gray-Scale Image Encoding Scheme." Communications in Theoretical Physics 69, no. 2 (February 2018): 215. http://dx.doi.org/10.1088/0253-6102/69/2/215.
Full textJavidi, Bahram, and Qing Tang. "Binary encoding of gray scale nonlinear joint transform correlators." Applied Optics 30, no. 11 (April 10, 1991): 1321. http://dx.doi.org/10.1364/ao.30.001321.
Full textYu, F. T. S., S. Jutamulia, and E. Tam. "Gray level pseudocolor encoding using a liquid crystal television." Journal of Optics 19, no. 3 (May 1988): 129–34. http://dx.doi.org/10.1088/0150-536x/19/3/004.
Full textZhang Shaoze, 张绍泽, 张建奇 Zhang Jianqi, 黄曦 Huang Xi, and 刘德连 Liu Delian. "Three-Dimensional Profile Data Representation Based on Gray Value Encoding." Chinese Journal of Lasers 42, no. 12 (2015): 1209001. http://dx.doi.org/10.3788/cjl201542.1209001.
Full textChakraborty, Uday K., and Cezary Z. Janikow. "An analysis of Gray versus binary encoding in genetic search." Information Sciences 156, no. 3-4 (November 2003): 253–69. http://dx.doi.org/10.1016/s0020-0255(03)00178-6.
Full textZhang, Hongxin, Hao Zhou, Jingyao Li, Yujing Qiao, and Wei Gao. "Research on encoding multi-gray-scale phase hologram and wavefront reconstruction." Applied Optics 55, no. 10 (March 30, 2016): 2701. http://dx.doi.org/10.1364/ao.55.002701.
Full textKahr, Walter HA, Jesse Hinckley, Ling Li, Hansjörg Schwertz, Hilary Christensen, Jesse W. Rowley, Fred G. Pluthero, et al. "Mutations in NBEAL2, encoding a BEACH protein, cause gray platelet syndrome." Nature Genetics 43, no. 8 (July 17, 2011): 738–40. http://dx.doi.org/10.1038/ng.884.
Full textYan, Jing, Wenjuan Li, Tingting Zhang, Junjun Zhang, Zhenlan Jin, and Ling Li. "The Correlation Between Gray Matter Volume and Verbal Episodic Memory Encoding." International Journal of Psychophysiology 168 (October 2021): S209. http://dx.doi.org/10.1016/j.ijpsycho.2021.07.566.
Full textDissertations / Theses on the topic "Gray encoding"
Kowalewski, Damian. "Edge-based encoding of gray-scale images." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=80305.
Full textKováč, Michal. "ANALÝZA MOŽNOSTÍ SIMULÁCIE A IMPLEMENTÁCIE AUTOSYNCHRÓNNYCH SUBSYSTÉMOV V OBVODOCH VLSI." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-233515.
Full textAnderson, Adam Lane. "Unitary Space-Time Transmit Diversity for Multiple Antenna Self-Interference Suppression." BYU ScholarsArchive, 2004. https://scholarsarchive.byu.edu/etd/154.
Full textOliveira, Marcos Antônio Almeida de. "Heurística aplicada ao problema árvore de Steiner Euclidiano com representação nó-profundidade-grau." Universidade Federal de Goiás, 2014. http://repositorio.bc.ufg.br/tede/handle/tede/4171.
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Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG
A variation of the Beasley (1992) algorithm for the Euclidean Steiner tree problem is presented. This variation uses the Node-Depth-Degree Encoding, which requires an average time of O(n) in operations to generate and manipulate spanning forests. For spanning tree problems, this representation has linear time complexity when applied to network design problems with evolutionary algorithms. Computational results are given for test cases involving instances up to 500 vertices. These results demonstrate the use of the Node-Depth-Degree in an exact heuristic, and this suggests the possibility of using this representation in other techniques besides evolutionary algorithms. An empirical comparative and complexity analysis between the proposed algorithm and a conventional representation indicates the efficiency advantages of the solution found.
É apresentada uma variação do algoritmo de Beasley (1992) para o Problema árvore de Steiner Euclidiano. Essa variação utiliza a Representação Nó-Profundidade-Grau que requer, em média, tempo O(n) em operações para gerar e manipular florestas geradoras. Para problemas de árvore geradora essa representação possui complexidade de tempo linear sendo aplicada em problemas de projeto de redes com algoritmos evolutivos. Resultados computacionais são dados para casos de teste envolvendo instâncias de até 500 vértices. Esses resultados demonstram a utilização da representação Nó-Profundidade-Grau em uma heurística exata, e isso sugere a possibilidade de utilização dessa representação em outras técnicas além de algoritmos evolutivos. Um comparativo empírico e da análise de complexidade entre o algoritmo proposto e uma representação convencional indica vantagens na eficiência da solução encontrada.
Faria, Danilo Alves Martins de. "Operador de recombinação EHR aplicado ao problema da árvore máxima." Universidade Federal de Goiás, 2013. http://repositorio.bc.ufg.br/tede/handle/tede/3655.
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Made available in DSpace on 2014-11-20T14:17:45Z (GMT). No. of bitstreams: 2 Dissertação - Danilo Alves Martins de Faria - 2013.pdf: 1188393 bytes, checksum: c56b169690f22bbbeaa2ee6fa46ade1c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013-10-23
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
Network Design Problems (NDPs) are present in many areas, such as electric power distribution, communication networks, vehicle routing, phylogenetic trees among others. Many NDPs are classified as NP-Hard problems. Among the techniques used to solve them, we highlight the Evolutionary Algorithms (EA). These algorithms simulate the natural evolution of the species. However, in its standard form EAs have limitations to solve large scale NDPs, or with very specific characteristics. To solve these problems, many researchers have studied specific forms of representation of NDPs. Among these stands we show Node-Depth-Degre Encoding (NDDE). This representation produces only feasible solutions, regardless of the network characteristics. NDDE has two mutation operators Preserve Ancestor Operator (PAO) and Ancestor Change Operator (CAO) and the recombination operator EHR (Evolutionary History Recombination Operator) that uses historical applications of mutation, and was applied to NDPs more than one tree and had good results. Thus, this work proposes adapt EHR for NDPs classics represented by a single tree. In addition, two evolutionary algorithms are developed: the AE-RNPG, which uses only NDDE, with mutation operators. And the AE-EHR, which makes use of mutation operators and recombination operator EHR to the One Max Tree Problem. The results showed that the AE-EHR obtained better solutions than the EA-RNPG for most instances analyzed.
Problemas de Projeto de Redes (PPRs) estão presentes em diversas áreas, tais como reconfiguração de sistemas de distribuição de energia elétrica, projetos de redes de comunicação, roteamento de veículos, reconstrução de árvores filogenéticas entre outros. Vários PPRs pertencem à classe de problemas NP-Difíceis. Dentre as técnicas utilizadas para resolvê-los, destacam-se os Algoritmos Evolutivos (AE), cujo processo de resolução de um problema simula a evolução natural das espécies. Entretanto, os AEs em sua forma padrão também possuem limitações quanto a PPRs de larga escala, ou com características muito específicas. Para solucionar esses problemas, diversas pesquisas têm estudado formas específicas de estruturas de dados dos PPRs. Dentre essas destaca-se a representação Nó-Profundidade-Grau (RNPG). Essa representação produz apenas soluções factíveis, independente da característica da rede. A RNPG possui dois operadores de mutação Preserve Ancestor Operator (PAO) e Change Ancestor Operator (CAO) e o operador de recombinação EHR (Evolutionary History Recombination Operator), que utiliza o histórico de aplicações dos operadores de mutação, o qual tem sido aplicado a PPRs com mais de uma árvore com bons resultados. Este trabalho propõem a adequação do EHR para PPRs clássicos de uma única árvore. Além disso, são desenvolvidos dois algoritmos evolutivos: o AE-RNPG, que utiliza a RNPG somente com os operadores de mutação; e o AE-EHR, que faz uso tanto dos operadores de mutação quanto do operador de recombinação EHR para o problema da Árvore máxima. Os resultados obtidos mostram que o AE-EHR obtém melhores soluções do que o AE-RNPG para a maioria das instâncias analisadas.
Chan, Hao-Ping, and 詹皓評. "A High-Speed Encoding Module for Gray and Binary Codes Transformation." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/7y837e.
Full text國立勤益科技大學
電子工程系
105
Bell Labs researcher Frank Gray proposed Gray code in 1940, so named Gray code in succeeding study. The code characteristics of the adjacent value is only one bit transition in difference. When the code value changes, Gray code unlike traditional binary code will not vary more than two bits in simultaneously. The property of Gray code implies is with less transient codes occurred due to various time delay of digital data paths in circuit realization. A modular 8-bit high-speed Gray code and binary code encoding circuit is proposed in this study, by using the concepts of carry select adder (CSA) and add one circuit to improve operating speed. The circuit is designed by using TSMC CMOS 90-nm process. The length of eight bit circuit is one module circuit. Three modules is in cascaded to realize 24 bit Gray-to-Binary transformation and vice vesa. Simulation results show that the improved circuit works successfully in 1 GHz under 24 bits length. In contrast to conventional design, the maximum operation speed of the traditional desogn is only capable of 500 MHz.
CHENG, FU-TENG, and 鄭富騰. "Built-in Self-Checking and Self-Repair for Binary-Gray Encoding/Decoding Chip." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/27sz73.
Full text國立勤益科技大學
電子工程系
107
In 1940, Bell Labs researcher Frank Gray proposed Gray code. The characteristic of the code is one-bit difference in two successive codes. The code is useful in reduction of glitch error due to signal time delay in chip. As feature size of CMOS technology scaling down, design of VLSI circuits become more complex and highly density in modern circuit system. Due to complexity of process, chip function sometime will be fail permanently. In addition, signal time delay within a chip often induces function transient fault. Therefore, fault tolerant techniques in highly reliable chip is more important. In this study, the built-in self-checking and self-repair capabilities for binary-Gray codes transformation is proposed. This code/decoded circuit can detect single fault within chip for any bit. When a fault occurs, the proposed circuit will be self-repaired automatically by backup circuit to retain coding/encoded successfully. Additionally, the design of circuit is with bit expandability to increase the flexibility of circuit applications. The performance of the circuit is verified by using HSPICE circuit simulator. This circuit has been realized in chip by using TSMC 0.18-μm 1P6M CMOS technology. Simulation results show the maximum operation frequency of 125 MHz. The average power dissipation of the circuit is 2.57 mW and 2.15 mW for encoder and decoder function respectively.
Jeng, Ming Der, and 鄭明德. "Power Estimation of Internal Nodes for Finite State Machine Using Gray Code Encoding in State Assignment." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/57456993492397944752.
Full text國立中山大學
電機工程研究所
84
The dynamic power of a FSM can be reduced if the count of bit change activity during the state transition is decreased by appropriate arrangements of the states. Accordingly, the total power disspation is also reduced. In the work, we compute the prob. for a FSM given the state transition prob. matrix and initial input signal. Then, using Gray encoding approach to assign the binary represention to each state. Though the result of simulations show that the Gray code enoding low power state assignment reduces almost 13.47% of total bit transition, it is still underestimated due to the ignorance of the reduction of transitions occurring at internal nodes. We take the transition activity of each internal node of the FSM into consideration. An estimation method, thus, is proposed to predict the more precise reduction ratio. Besides, a stablized upper bound of reduction ratio of transition activity can also be computed.
Book chapters on the topic "Gray encoding"
Chakraborty, Uday K. "Gray and Binary Encoding in the (1+1)-EA." In Neural Information Processing, 242–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30499-9_36.
Full textChang, Chin-Chen, Chia-Chen Lin, and Yi-Hui Chen. "A Secure Data Embedding Scheme Using Gray-Code Computation and SMVQ Encoding." In Studies in Computational Intelligence, 63–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02335-4_4.
Full textFu, Yeh Fen, L. H. Shyu, Y. T. Chen, Wen Yuh Jywe, and C. H. Liu. "A New Concept of Optical Encoder Displacement Sensors: Gray Encoding Patterns and a Curve Fitting Method." In Materials Science Forum, 349–54. Stafa: Trans Tech Publications Ltd., 2006. http://dx.doi.org/10.4028/0-87849-990-3.349.
Full textGilmore, M. S. "Molecular Cloning of Genes Encoding Gram-Positive Virulence Factors." In Current Topics in Microbiology and Immunology, 219–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-70586-1_12.
Full textWhitley, Darrell, and Jonathan E. Rowe. "Gray, Binary and Real Valued Encodings: Quad Search and Locality Proofs." In Foundations of Genetic Algorithms, 21–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11513575_2.
Full textFerdous, Hasnaeen, Raihan Uddin, and Swakkhar Shatabda. "Subcellular Localization of Gram-Negative Proteins Using Label Powerset Encoding." In Advances in Intelligent Systems and Computing, 529–40. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1951-8_48.
Full textSuzuki, Tetsuya. "Introduction of N-gram into a Run-Length Encoding Based ASCII Art Extraction Method." In Current Trends in Web Engineering, 28–39. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24800-4_3.
Full textSaha, Suprativ, and Tanmay Bhattacharya. "An Approach to Find Proper Execution Parameters of n-Gram Encoding Method Based on Protein Sequence Classification." In Communications in Computer and Information Science, 294–303. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9942-8_28.
Full textSaha, Suprativ, and Tanmay Bhattacharya. "A Novel Approach to Find the Saturation Point of n-Gram Encoding Method for Protein Sequence Classification Involving Data Mining." In International Conference on Innovative Computing and Communications, 101–8. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2354-6_12.
Full textSemary, Noura A. "An Efficient Color Image Encoding Scheme Based on Colorization." In Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies, 216–33. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6030-4.ch012.
Full textConference papers on the topic "Gray encoding"
Lin, Kuang Tsan. "Gray-Image Encryption Using Multiplex Encoding Method." In 2008 3rd International Conference on Innovative Computing Information and Control. IEEE, 2008. http://dx.doi.org/10.1109/icicic.2008.299.
Full textSrikantan, Geetha, Stephen W. Lam, and Sargur N. Srihari. "Gradient-based contour encoding for gray-scale character recognition." In IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, edited by Donald P. D'Amato. SPIE, 1993. http://dx.doi.org/10.1117/12.143609.
Full textChang, Yeim-Kuan, and Cheng-Chien Su. "Efficient TCAM Encoding Schemes for Packet Classification Using Gray Code." In IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference. IEEE, 2007. http://dx.doi.org/10.1109/glocom.2007.353.
Full textHoriuchi, Takahiko, Xu Wen, and Keita Hirai. "REVERSIBLE COLOR-TO-GRAY MAPPING WITH RESISTANCE TO JPEG ENCODING." In 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI). IEEE, 2018. http://dx.doi.org/10.1109/ssiai.2018.8470306.
Full textWang, Mingzhen, Ling Wang, and Hongsheng Zhong. "Pipelined Gray encoding scheme for ultra-high sampling rate Flash ADCs." In 2013 International Conference on Computational Problem-solving (ICCP). IEEE, 2013. http://dx.doi.org/10.1109/iccps.2013.6893528.
Full textAmalraj, D. J., N. Sundararajan, and Goutam Dhar. "Data structure based on Gray code encoding for graphics and image processing." In San Diego '90, 8-13 July, edited by Andrew G. Tescher. SPIE, 1990. http://dx.doi.org/10.1117/12.23516.
Full textMambou, Elie N., and Theo G. Swart. "Encoding and decoding of balanced q-ary sequences using a Gray code prefix." In 2016 IEEE International Symposium on Information Theory (ISIT). IEEE, 2016. http://dx.doi.org/10.1109/isit.2016.7541325.
Full textMutter, Kussay Nugamesh, Zubir Mat Jafri, and Azlan Abdul Aziz. "Automatic Fingerprint Identification Using Gray Hopfield Neural Network Improved by Run-Length Encoding." In 2008 5th International Conference on Computer Graphics, Imaging and Visualisation (CGIV). IEEE, 2008. http://dx.doi.org/10.1109/cgiv.2008.25.
Full textLi, Gaoping. "Accelerating Fractal Image Encoding Based on Gray Value Moment Features of Normalized Block." In 2008 International Symposium on Computer Science and Computational Technology. IEEE, 2008. http://dx.doi.org/10.1109/iscsct.2008.344.
Full textParker, James R., and D. Horsley. "Grey-level encoding of openings and closings." In Optical Tools for Manufacturing and Advanced Automation, edited by Robert A. Melter and Angela Y. Wu. SPIE, 1993. http://dx.doi.org/10.1117/12.165009.
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