Literatura científica selecionada sobre o tema "Convolutional code-word"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Consulte a lista de atuais artigos, livros, teses, anais de congressos e outras fontes científicas relevantes para o tema "Convolutional code-word".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Artigos de revistas sobre o assunto "Convolutional code-word"
Sidorenko, A. A. "Decoding of the turbo code created on the basis of the block code using the syndrome grid". Journal of Physics: Conference Series 2388, n.º 1 (1 de dezembro de 2022): 012029. http://dx.doi.org/10.1088/1742-6596/2388/1/012029.
Texto completo da fonteWang, Yilin, Siqing Xue e Jun Song. "A Malicious Webpage Detection Method Based on Graph Convolutional Network". Mathematics 10, n.º 19 (25 de setembro de 2022): 3496. http://dx.doi.org/10.3390/math10193496.
Texto completo da fonteRamanna, Dasari, e V. Ganesan. "Low-Power VLSI Implementation of Novel Hybrid Adaptive Variable-Rate and Recursive Systematic Convolutional Encoder for Resource Constrained Wireless Communication Systems". International Journal of Electrical and Electronics Research 10, n.º 3 (30 de setembro de 2022): 523–28. http://dx.doi.org/10.37391/ijeer.100320.
Texto completo da fonteEt.al, Vishaal Saravanan. "Automated Web Design And Code Generation Using Deep Learning". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, n.º 6 (10 de abril de 2021): 364–73. http://dx.doi.org/10.17762/turcomat.v12i6.1401.
Texto completo da fonteFarid, Ahmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin e Laila A. Abd-Elmegid. "Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM)". PeerJ Computer Science 7 (16 de novembro de 2021): e739. http://dx.doi.org/10.7717/peerj-cs.739.
Texto completo da fonteHsu, Jia-Lien, Teng-Jie Hsu, Chung-Ho Hsieh e Anandakumar Singaravelan. "Applying Convolutional Neural Networks to Predict the ICD-9 Codes of Medical Records". Sensors 20, n.º 24 (11 de dezembro de 2020): 7116. http://dx.doi.org/10.3390/s20247116.
Texto completo da fonteBanerjee, Suman, e Mitesh M. Khapra. "Graph Convolutional Network with Sequential Attention for Goal-Oriented Dialogue Systems". Transactions of the Association for Computational Linguistics 7 (novembro de 2019): 485–500. http://dx.doi.org/10.1162/tacl_a_00284.
Texto completo da fonteRao, Jinfeng, Wei Yang, Yuhao Zhang, Ferhan Ture e Jimmy Lin. "Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 232–40. http://dx.doi.org/10.1609/aaai.v33i01.3301232.
Texto completo da fonteSimistira Liwicki, Foteini, Vibha Gupta, Rajkumar Saini, Kanjar De e Marcus Liwicki. "Rethinking the Methods and Algorithms for Inner Speech Decoding and Making Them Reproducible". NeuroSci 3, n.º 2 (19 de abril de 2022): 226–44. http://dx.doi.org/10.3390/neurosci3020017.
Texto completo da fonteZhang, Min, Yujin Yan, Hai Wang e Wei Zhao. "An Algorithm for Natural Images Text Recognition Using Four Direction Features". Electronics 8, n.º 9 (31 de agosto de 2019): 971. http://dx.doi.org/10.3390/electronics8090971.
Texto completo da fonteTeses / dissertações sobre o assunto "Convolutional code-word"
Bellard, Marion. "Influence du mapping sur la reconnaissance d'un système de communication". Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066008.
Texto completo da fonteThe context of this thesis is the recognition of communication systems in a non-cooperative context. We are interested in the convolutional code reconstruction problem and in the constellation labeling reconstruction (the mapping used to associate a binary sequence to a modulated signal). We have defined a new statistical method for detecting if a given binary sequence is a noisy convolutional code-word obtained from an unknown convolutional code. It consists in forming blocks of sequence which are big enough to contain the support of a parity check equation and counting the number of blocks which are equal. It gives the length of the convolutional code without knowledge of the constellation labeling. This method can also be used to reconstruct the dual of a convolutional code when the constellation labeling is known. Moreover we propose a constellation labeling recognition algorithm using some equivalence classes. Two types of classes are defined: linear and affine. We observe a noisy signal which is partially demodulated (with a default labeling) and assume that the data are coded by a convolutional encoder. Thus we use the reconstruction of a code as a test and run through the classes which reveal a code structure. This classification improves the complexity of the search for small constellations (4-PSK and 8-PSK). In case of 16-QAM to 256-QAM constellations we apply the algorithm to Gray or quasi-Gray labelings. The algorithm does not give a unique result but it allows to find a small set of possible constellation labelings from noisy data
Capítulos de livros sobre o assunto "Convolutional code-word"
Lei, Jing Sheng, Chen Si Cong Zhu, Sheng Ying Yang, Guan Mian Liang, Cong Hu e Wei Song. "Interpretable Dual-Feature Recommender System Using Reviews1". In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210175.
Texto completo da fonte