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NARMAX models

  • Install Guide
  • A brief introduction to NARMAX models.
  • User Guide
  • Contributing
  • Jupyter notebooks
    • Presenting main functionality
    • Multiple Inputs usage
    • Information Criteria - Examples
    • Important notes and examples of how to use Extended Least Squares
    • Setting specific lags
    • Parameter Estimation
    • Using the Meta-Model Structure Selection (MetaMSS) algorithm for building Polynomial NARX models
    • Using the Accelerated Orthogonal Least-Squares algorithm for building Polynomial NARX models
    • Example: F-16 Ground Vibration Test benchmark
    • Building NARX Neural Network using Sysidentpy
    • Building NARX models using general estimators
    • Simulate a Predefined Model
    • System Identification Using Adaptative Filters
    • Identification of an electromechanical system
    • Example: N-steps-ahead prediction - F-16 Ground Vibration Test benchmark
  • Changes in SysIdentPy
  • Codes
Theme by the Executable Book Project

All modules for which code is available

  • sysidentpy.base
  • sysidentpy.general_estimators.narx
  • sysidentpy.metaheuristics.bpsogsa
  • sysidentpy.metrics._regression
  • sysidentpy.parameter_estimation.estimators
  • sysidentpy.polynomial_basis.metamss
  • sysidentpy.polynomial_basis.narmax
  • sysidentpy.polynomial_basis.simulation
  • sysidentpy.residues.residues_correlation
  • sysidentpy.utils._check_arrays
  • sysidentpy.utils.generate_data

De Wilson Rocha, Luan Pascoal, Samuel Oliveira, Samir Martins
© direito autoral 2020, Wilson Rocha, Luan Pascoal, Samuel Oliveira, Samir Martins.