In each iteration, the algorithm eliminates the linear parameters of the model, then updates the nonlinear parameters through the gradient descent (GD) ...
In each iteration, the algorithm eliminates the linear parameters of the model, then updates the nonlinear parameters through the gradient descent (GD) ...
This paper extends recent results by the first author and T. Pock (ICG, TU Graz, Austria) on the acceleration of alternating minimization techniques for ...
Aitken's delta-squared process or Aitken extrapolation is a series acceleration method, used for accelerating the rate of convergence of a sequence.
Missing: variable projection
In each iteration, the algorithm eliminates the linear parameters of the model, then updates the nonlinear parameters through the gradient descent (GD) ...
The paper describes the application of a variation of the Aitken acceleration method for nonlinear problems. The approach computes an improved estimate of ...
Mar 23, 2023 · In order to speed up the convergence of the gradient descent algorithm, the Aitken acceleration technique is introduced in the algorithms, which ...
People also ask
What is the Aitken method of algorithm?
What is affine projection algorithm?
Aitken-based Acceleration Estimation Algorithms for a Nonlinear Model ...
link.springer.com › article
Sep 2, 2021 · This paper studies some parameter estimation algorithms for a class of nonlinear models with exponential terms, ie, the radial basis function-based state- ...
A variable projection algorithm based on the Aitken method is proposed, which takes into consideration of the multipath effect error with the aim at ...
This algorithm leverages the convergence and maximum likelihood estimation properties of the EM algorithm [40] to address parameter estimation issues associated ...