We introduce a novel approach to the blind signal separation (BSS) problem that is capable of jointly estimating the probability density function (pdf) of the source signals and the unmixing matrix. We demonstrate that, using a kernel density estimation based Projection Pursuit (PP) algorithm, it is possible to extract, from instantaneous mixtures, independent sources that are arbitrarily distr...

The present work presents a novel approach for semi-analytic adjoint sensitivity-based design optimization nonproportional fatigue damage. In order to apply damage in optimizations, an essential part is calculate correct sensitivities. However, this not straight forward since calculation typically include rainflow counting and critical plane search algorithms. Therefore, no derivatives are dire...

Network data are becoming increasingly available, and so there is a need to develop suitable methodology for statistical analysis. Networks can be represented as graph Laplacian matrices, which type of manifold-valued data. Our main objective estimate regression curve from sample matrices conditional on set Euclidean covariates, example, in dynamic networks where the covariate time. We an adapt...