We propose a Newton-CG primal proximal point algorithm for solving large scale log-determinant optimization problems. Our algorithm employs the essential ideas of the proximal poi...
— In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SIM...
In previous work, a water-filling algorithm was proposed which sought to minimize the mean square error (MSE) at any given time by optimally choosing the gains (i.e. step-sizes) ...
Like its linear counterpart, the Kernel Least Mean Square (KLMS) algorithm is also becoming popular in nonlinear adaptive filtering due to its simplicity and robustness. The “k...
In this work, we propose adaptive frequency-domain biased estimation algorithms with mechanisms to automatically adjust the shrinkage factors. The proposed estimation algorithms i...