Literatura científica selecionada sobre o tema "Nonlinearity equalization"
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Artigos de revistas sobre o assunto "Nonlinearity equalization"
Golani, Ori, Meir Feder e Mark Shtaif. "Equalization Methods for Out-of-Band Nonlinearity Mitigation in Fiber-Optic Communications". Applied Sciences 9, n.º 3 (2 de fevereiro de 2019): 511. http://dx.doi.org/10.3390/app9030511.
Texto completo da fonteChen, Yuanjie. "Blind equalization with criterion with memory nonlinearity". Optical Engineering 31, n.º 6 (1992): 1200. http://dx.doi.org/10.1117/12.57519.
Texto completo da fonteChen, Qianwen, Xiong Chen, David J. Pommerenke e Ming Yu. "Balanced Intermodulation Reference With Flat Frequency Response Using Nonlinearity Equalization". IEEE Transactions on Electromagnetic Compatibility 62, n.º 6 (dezembro de 2020): 2634–37. http://dx.doi.org/10.1109/temc.2020.2981462.
Texto completo da fonteMiao, Pu, Weibang Yin, Hui Peng e Yu Yao. "Study of the Performance of Deep Learning-Based Channel Equalization for Indoor Visible Light Communication Systems". Photonics 8, n.º 10 (18 de outubro de 2021): 453. http://dx.doi.org/10.3390/photonics8100453.
Texto completo da fonteRuqi Zhang, Ruqi Zhang, Jianfeng Li Jianfeng Li, Zhitong Huang Zhitong Huang e Yuefeng Ji Yuefeng Ji. "Adaptive frequency domain pre-equalization for white-LED nonlinearity in OFDM-based visible light communication systems". Chinese Optics Letters 13, n.º 7 (2015): 072302–72305. http://dx.doi.org/10.3788/col201513.072302.
Texto completo da fonteKumar Orappanpara Soman, Sunish. "A tutorial on fiber Kerr nonlinearity effect and its compensation in optical communication systems". Journal of Optics 23, n.º 12 (22 de novembro de 2021): 123502. http://dx.doi.org/10.1088/2040-8986/ac362a.
Texto completo da fonteSiuzdak, Jerzy. "Comparison of the Nonlinear Dynamic Pre- and Post-LED Equalization". Sensors 22, n.º 5 (24 de fevereiro de 2022): 1782. http://dx.doi.org/10.3390/s22051782.
Texto completo da fonteScarano, Gaetano, Andrea Petroni, Mauro Biagi e Roberto Cusani. "Blind Fractionally Spaced Channel Equalization for Shallow Water PPM Digital Communications Links". Sensors 19, n.º 21 (23 de outubro de 2019): 4604. http://dx.doi.org/10.3390/s19214604.
Texto completo da fonteAsif, Rameez, Rabeea Basir e Ramshah Ahmad. "Signal Processing Algorithms for Down-Stream Traffic in Next Generation 10 Gbit/s Fixed-Grid Passive Optical Networks". Advances in OptoElectronics 2014 (22 de junho de 2014): 1–4. http://dx.doi.org/10.1155/2014/296781.
Texto completo da fonteMauda, R., e M. Pinchas. "16QAM Blind Equalization via Maximum Entropy Density Approximation Technique and Nonlinear Lagrange Multipliers". Scientific World Journal 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/548714.
Texto completo da fonteTeses / dissertações sobre o assunto "Nonlinearity equalization"
Benammar, Bouchra. "Formes d'ondes avancées et traitements itératifs pour les canaux non linéaires satellites". Phd thesis, Toulouse, INPT, 2014. http://oatao.univ-toulouse.fr/13567/1/Benammar.pdf.
Texto completo da fonteShahkarami, Abtin. "Complexity reduction over bi-RNN-based Kerr nonlinearity equalization in dual-polarization fiber-optic communications via a CRNN-based approach". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT034.
Texto completo da fonteThe impairments arising from the Kerr nonlinearity in optical fibers limit the achievable information rates in fiber-optic communication. Unlike linear effects, such as chromatic dispersion and polarization-mode dispersion, which can be compensated via relatively simple linear equalization at the receiver, the computational complexity of the conventional nonlinearity mitigation techniques, such as the digital backpropagation, can be substantial. Neural networks have recently attracted attention, in this context, for low-complexity nonlinearity mitigation in fiber-optic communications. This Ph.D. dissertation deals with investigating the recurrent neural networks to efficiently compensate for the nonlinear channel impairments in dual-polarization long-haul fiber-optic transmission. We present a hybrid convolutional recurrent neural network (CRNN) architecture, comprising a convolutional neural network (CNN) -based encoder followed by a recurrent layer working in tandem. The CNN-based encoder represents the shortterm channel memory arising from the chromatic dispersion efficiently, while transitioning the signal to a latent space with fewer relevant features. The subsequent recurrent layer is implemented in the form of a unidirectional vanilla RNN, responsible for capturing the long-range interactions neglected by the CNN encoder. We demonstrate that the proposed CRNN achieves the performance of the state-of-theart equalizers in optical fiber communication, with significantly lower computational complexity depending on the system model. Finally, the performance complexity trade-off is established for a number of models, including multi-layer fully-connected neural networks, CNNs, bidirectional recurrent neural networks, bidirectional long short-term memory (bi-LSTM), bidirectional gated recurrent units, convolutional bi-LSTM models, and the suggested hybrid model
Bartholomew, David Ray. "Design of a High Speed Mixed Signal CMOS Mutliplying Circuit". Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd362.pdf.
Texto completo da fonteLivros sobre o assunto "Nonlinearity equalization"
Gutiérrez, Alberto. Equalization and detection for digital communication over nonlinear bandlimited satellite communication channels. Las Cruces, N.M: New Mexico State University, 1995.
Encontre o texto completo da fonteAlberto, Gutiérrez. Equalization and detection for digital communication over nonlinear bandlimited satellite communication channels. Las Cruces, N.M: New Mexico State University, 1995.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Nonlinearity equalization"
Majumder, Saikat. "Wavelet Neural Networks and Equalization of Nonlinear Satellite Communication Channel". In Applications of Artificial Neural Networks for Nonlinear Data, 207–26. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4042-8.ch009.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Nonlinearity equalization"
Riant, I., S. Borne e P. Sansonetti. "Asymetrical UV-Written Fibre Fabry-Perot for WDM Soliton Frequency-Guiding and Equalization". In Photosensitivity and Quadratic Nonlinearity in Glass Waveguides. Washington, D.C.: Optica Publishing Group, 1995. http://dx.doi.org/10.1364/pqn.1995.sab.4.
Texto completo da fonteZhang, Yang, e Saleem A. Kassam. "Blind equalization using coarse quantizer BSS nonlinearity". In 2011 45th Annual Conference on Information Sciences and Systems (CISS 2011). IEEE, 2011. http://dx.doi.org/10.1109/ciss.2011.5766222.
Texto completo da fonteKoike-Akino, T., Ye Wang, D. S. Millar, K. Kojima e K. Parsons. "Neural turbo equalization to mitigate fiber nonlinearity". In 45th European Conference on Optical Communication (ECOC 2019). Institution of Engineering and Technology, 2019. http://dx.doi.org/10.1049/cp.2019.0803.
Texto completo da fonteRosenkranz, Werner, e Johannes von Hoyningen-Huene. "Nonlinearity compensation and equalization in access networks". In 2012 Opto-Electronics and Communications Conference (OECC). IEEE, 2012. http://dx.doi.org/10.1109/oecc.2012.6276521.
Texto completo da fonteSilva, Edson Porto da, e Metodi Plamenov Yankov. "Adaptive Turbo Equalization of Probabilistically Shaped Constellations". In Optical Fiber Communication Conference. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/ofc.2023.th2a.26.
Texto completo da fonteXia, Chunmin, e Werner Rosenkranz. "Mitigation of Optical Intrachannel Nonlinearity Using Nonlinear Electrical Equalization". In 2006 32nd European Conference on Optical Communications - (ECOC 2006). IEEE, 2006. http://dx.doi.org/10.1109/ecoc.2006.4801152.
Texto completo da fonteLi, Xiangyu, Hanjie Chen, Shangbin Li, Qian Gao, Chen Gong e Zhengyuan Xu. "Volterra-based nonlinear equalization for nonlinearity mitigation in organic VLC". In 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, 2017. http://dx.doi.org/10.1109/iwcmc.2017.7986356.
Texto completo da fonteBeppu, S., K. Saito, N. Yoshikane e T. Tsuritani. "Fiber Nonlinearity Equalization with a Quantum-Enhanced Support Vector Machine". In 2022 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC). IEEE, 2022. http://dx.doi.org/10.23919/oecc/psc53152.2022.9850116.
Texto completo da fonteLei, Lei, Jianglong Lian, Ketong Zhang e Yutong Nan. "Post-Equalization Technique to Mitigate LED Nonlinearity in VLC Systems". In 2023 IEEE International Conference on Image Processing and Computer Applications (ICIPCA). IEEE, 2023. http://dx.doi.org/10.1109/icipca59209.2023.10257998.
Texto completo da fonteCho, Junho, e Son Thai Le. "Volterra Equalization to Compensate for Transceiver Nonlinearity: Performance and Pitfalls". In Optical Fiber Communication Conference. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/ofc.2022.w2a.36.
Texto completo da fonte