Title :
Analysis on extended kernel recursive least squares algorithm
Author :
Pingping Zhu ; Principe, Jose C.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
In this paper, the extended kernel recursive least squares (Ex-KRLS) algorithm is reviewed and analyzed. We point out that the Theorem 1 in [10] is not always correct for general cases. Furthermore, the Ex-KRLS algorithm for tracking model is just a random walk KRLS algorithm. Finally, this algorithm is explained as a special Kalman filter in the reproducing kernel Hilbert space.
Keywords :
Hilbert spaces; Kalman filters; least squares approximations; random processes; Ex-KRLS algorithm; Kalman filter; extended kernel recursive least squares algorithm; kernel Hilbert space; random walk KRLS algorithm; tracking model; Algorithm design and analysis; Heuristic algorithms; Hilbert space; Kalman filters; Kernel; Noise; Vectors;
Conference_Titel :
Neural Networks (IJCNN), The 2013 International Joint Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4673-6128-6
DOI :
10.1109/IJCNN.2013.6706865
