Robust linear decentralized tracking of a time varying sparse parameter is studied in multiple-input multiple-output (MIMO) wireless sensor network (WSN) under channel state information (CSI) uncertainty. Initially, assuming perfect CSI availability, novel Bayesian learning-based Kalman filtering (SBL-KF) framework developed order to track the parameter. Subsequently, an optimization problem fo...

A novel adaptive method to achieve both path following and formation moving along desired orbits in the presence of a spatio-temporal flowfield is presented. The general flow with unknown time-varying parameters. so-called \emph{congelation variables} used estimate parameters, which do not have any restrictions on rate their variation. asymptotic properties resulting system are studied detail. ...

in this paper the numerical analysis of flow and time dependent heat transfer of micro-tube conveying nanofluid in laminar flow is investigated. in this study, convection heat transfer of nanofluid and base fluid and transient analysis for time-varying heat flux for time step of 0.0001 second are elucidated. it is observed that the pumping power of nanofluid flowing and the maximum temperature ...

Consensus problems in time-varying networks are studied in this paper. We consider two cases. In the first case, the networks are basically connected and the conditions for reaching consensus are described by means of the algebraic properties of connectivity for network graph. In the second case, the networks are possibly disconnected all time. A concept called integral connectivity of networks...

Tensors are effective representations for complex and time-varying networks. The factorization of a tensor provides a high-quality low-rank compact basis for each dimension of the tensor, which facilitates the interpretation of important structures of the represented data. Many existing tensor factorization (TF) methods assume there is one tensor that needs to be decomposed to low-rank factors....