The systems described by partial differential equations with different types of delays
Systems of partial differential equations (PDE) and ordinary differential equations (ODE) are studied from the point of view of Dynamical systems methods. Many problems from biology, chemistry, mechanics, control, information transmission, economics and other fields are changing in time and so they can be described by different types of Dynamical systems. It is well understood […]
Rationality and Deliberation
Rapid development of information and computer technology as well as availability of multiple, very frequently incompatible, informational sources have caused that decision makers (both humans and devices) are overloaded with information. Their imperfectness (i.e. limited cognitive, informational and evaluational capabilities) is confronted with decision making (DM) of growing complexity with incomplete DM preferences and imprecise […]
Bayesian regularization and inference for linear and bilinear models
Linear and bilinear models arise in many research areas including statistics, signal processing, machine learning, approximation theory, or image analysis. In cases when the problem of interest is ill-conditioned or suffers from separation ambiguity, the classical solutions such as ordinary least squares or non-negative matrix factorization fail and additional information is needed for acceptable solution. […]
Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI)
Rapid development of information and computer technology as well as availability of multiple, very frequently incompatible, informational sources have caused that decision makers (both humans and devices) are overloaded with information. Their imperfectness (i.e. limited cognitive, informational and evaluational capabilities) is confronted with decision making (DM) of growing complexity with incomplete DM preferences and imprecise […]
Distributed dynamic estimation in diffusion networks
The project aims to develop a dynamic distributed estimation framework, intended for fully distributed low-cost parameter estimation of stationary signals and reduced-complexity tracking of nonstationary processes. Being designed for diffusion networks, where each network node can use information provided by neighbor nodes, it will not rely on the existence of a dedicated fusion center, nor […]