Fifty years of MIMO detection: The road to large-scale MIMOs

S Yang, L Hanzo - IEEE communications surveys & tutorials, 2015 - ieeexplore.ieee.org
The emerging massive/large-scale multiple-input multiple-output (LS-MIMO) systems that
rely on very large antenna arrays have become a hot topic of wireless communications …

Data fusion in cyber-physical-social systems: State-of-the-art and perspectives

P Wang, LT Yang, J Li, J Chen, S Hu - Information Fusion, 2019 - Elsevier
Abstract Cyber-Physical-Social systems (CPSSs) are the extension of Cyber-Physical
systems (CPS), which seamlessly integrate cyber space, physical space and social space …

Bayesian learning and inference in recurrent switching linear dynamical systems

S Linderman, M Johnson, A Miller… - Artificial intelligence …, 2017 - proceedings.mlr.press
Many natural systems, such as neurons firing in the brain or basketball teams traversing a
court, give rise to time series data with complex, nonlinear dynamics. We can gain insight …

Survey of maneuvering target tracking. Part I. Dynamic models

XR Li, VP Jilkov - IEEE Transactions on aerospace and …, 2003 - ieeexplore.ieee.org
This is the first part of a comprehensive and up-to-date survey of the techniques for tracking
maneuvering targets without addressing the so-called measurement-origin uncertainty. It …

Multitarget Bayes filtering via first-order multitarget moments

RPS Mahler - IEEE Transactions on Aerospace and Electronic …, 2003 - ieeexplore.ieee.org
The theoretically optimal approach to multisensor-multitarget detection, tracking, and
identification is a suitable generalization of the recursive Bayes nonlinear filter. Even in …

[Књига][B] Dynamic bayesian networks: representation, inference and learning

KP Murphy - 2002 - search.proquest.com
Modelling sequential data is important in many areas of science and engineering. Hidden
Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they …

[Књига][B] Continuous-time Markov jump linear systems

OL do Valle Costa, MD Fragoso, MG Todorov - 2012 - books.google.com
It has been widely recognized nowadays the importance of introducing mathematical
models that take into account possible sudden changes in the dynamical behavior of a high …

Gaussian filters for nonlinear filtering problems

K Ito, K **
M Kaess, A Ranganathan… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
In this paper, we present incremental smoothing and map** (iSAM), which is a novel
approach to the simultaneous localization and map** problem that is based on fast …

Particle filters for positioning, navigation, and tracking

F Gustafsson, F Gunnarsson… - … on signal processing, 2002 - ieeexplore.ieee.org
A framework for positioning, navigation, and tracking problems using particle filters
(sequential Monte Carlo methods) is developed. It consists of a class of motion models and …