Improving adaptation/learning transients using a dynamic adaptation gain/learning rate - Theoretical and experimental results*

Author:

Landau Ioan Doré1,Airimitoaie Tudor-Bogdan2,Vau Bernard3,Buche Gabriel1

Affiliation:

1. Univ. Grenoble Alpes,CNRS, Grenoble INP, GIPSA-lab,Grenoble,France,38000

2. Univ. Bordeaux,CNRS, Bordeaux INP, IMS,Talence,France,33405

3. IXBLUE,Bonneuil-sur-Marne,France,12 avenue des coquelicots, 94385

Publisher

IEEE

Reference17 articles.

1. A survey on algorithms for training artificial neural networks;livieris;University of Patras Tech Rep,2014

2. Adaptive feedforward compensation algorithms for active vibration control with mechanical coupling

3. A method for solving a convex programming problem with convergence rate 0(1/k2);nesterov;Sov Math Dockl,1983

4. Gradient methods for the optimization of dynamical systems containing neural networks

5. A Youla–Kucera parametrized adaptive feedforward compensator for active vibration control with mechanical coupling

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