We consider Bayesian detection/classification of discrete random parameters that are strongly dependent locally due to some deterministic local constraint. Based on the recently ...
Georg Kail, Jean-Yves Tourneret, Franz Hlawatsch, ...
A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
— One of the unique characteristics of ultra-wideband channels is the clustering phenomenon resolved by the ultra-wide signal bandwidth. Channel structures extended from the Sale...
Wei-De Wu, Chung-Hsuan Wang, Chi-Chao Chao, Klaus ...
This paper presents a computational approach for the frequency-domain identification of multivariable, discrete-time transfer function models based on a cost function minimization...
Background: Current approaches to parameter estimation are often inappropriate or inconvenient for the modelling of complex biological systems. For systems described by nonlinear ...