Publications Repository - Gdańsk University of Technology

Accurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately chosen basis functions. The paper shows that tracking performance of the resulting local basis function estimation algorithms can be further improved by means of regularization. The method is illustrated by an important recent application - identification of fast time-varying acoustic channels used in underwater communication.

Authors

• prof. dr hab. inż. Maciej Niedźwiecki link open in new tab ,
• dr inż. Artur Gańcza link open in new tab ,
• dr inż. Piotr Kaczmarek link open in new tab