Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Although the linear mean-squared error (MSE) complex-DFT estimator, i.e., the Wiener filter, is well-known, its magnitude-DFT (MDFT) counterpart has never been considered in the ...