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Experimental Results on the Impact of Memory in Neural Networks for Spectrum Prediction in Land Mobile Radio Bands.

, , , , and . IEEE Trans. Cogn. Commun. Netw., 6 (2): 771-782 (2020)

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Neural Network Based Spectrum Prediction in Land Mobile Radio Bands for IoT deployments., , , and . IM, page 31-36. IFIP, (2019)Spatio-Temporally Constrained Reconstruction for Hyperpolarized Carbon-13 MRI Using Kinetic Models., , , , , , , , , and 4 other author(s). IEEE Trans. Med. Imaging, 37 (12): 2603-2612 (2018)Experimental Results on the Impact of Memory in Neural Networks for Spectrum Prediction in Land Mobile Radio Bands., , , , and . IEEE Trans. Cogn. Commun. Netw., 6 (2): 771-782 (2020)An Improvement to Test Case Failure Prediction in the Context of Test Case Prioritization., , , , and . PROMISE, page 80-89. ACM, (2018)Predicting Commentaries on a Financial Report with Recurrent Neural Networks., , and . Canadian AI, volume 11489 of Lecture Notes in Computer Science, page 531-542. Springer, (2019)Lagrangian methods for approximating the viability kernel in high-dimensional systems., , , , and . Autom., 49 (7): 2017-2029 (2013)A note on optimal experiment design for nonlinear systems using dynamic programming., and . CoRR, (2015)Optimal experiment design for physiological parameter estimation using hyperpolarized carbon-13 magnetic resonance imaging., , and . ACC, page 5770-5775. IEEE, (2015)Simulation-Based Reachability Analysis for Nonlinear Systems Using Componentwise Contraction Properties., and . Principles of Modeling, volume 10760 of Lecture Notes in Computer Science, page 61-76. Springer, (2018)Exploiting Symmetry for Discrete-Time Reachability Computations., and . IEEE Control. Syst. Lett., 2 (2): 213-217 (2018)