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Forecasting Nonlinear Systems with LSTM: Analysis and Comparison with EKF
2021
Sensors
Certain difficulties in path forecasting and filtering problems are based in the initial hypothesis of estimation and filtering techniques. Common hypotheses include that the system can be modeled as linear, Markovian, Gaussian, or all at one time. Although, in many cases, there are strategies to tackle problems with approaches that show very good results, the associated engineering process can become highly complex, requiring a great deal of time or even becoming unapproachable. To have tools
doi:10.3390/s21051805
pmid:33807681
fatcat:nlke3wmwznhszk3deq3ilxynpy