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Using Neural Networks with data Quantization for time Series Analysis in LHC Superconducting Magnets

:// , (in press). Graves, A. (2012). Neural Networks , Springer, Berlin/Heidelberg. Greff, K., Srivastava, R.K., Koutník, J., Steunebrink, B.R. and Schmidhuber, J. (2015). LSTM: A search space odyssey, ArXiv 1503.04069 [cs.NE]. Han, S., Kang, J., Mao, H., Hu, Y., Li, X., Li, Y., Xie, D., Luo, H., Yao, S., Wang, Y., Yang, H. and Dally, W. B.J. (2017). ESE: Efficient speech recognition engine with sparse LSTM on FPGA, Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA’17), Monterey, CA, USA , pp. 75

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Applied mathematics and nonlinear sciences in the war on cancer

eradicate as much disease as possible and provide tumor tissue for histological and genetic diagnosis. Nuclear medicine is involved in the use of nuclear isotopes to image not only function but tumor metabolism and proliferation status. Finally other medical specialists work on specific cancers depending on their location. Such a complex disease cannot be described completely by models that are too simple. In fact, this is one of the major criticisms made by biologists to mathematical models. They are typically trained to consider all the complexities of a system

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