We review some advances of the particle filtering (PF) algorithm that have been achieved in
the last decade in the context of target tracking, with regard to either a single target or …

Motivated by the increasing availability and quality of miniaturized sensors, computers, and
wireless communication devices and given their enormous potential, the use of wireless …

In this brief, we investigate online training of long short term memory (LSTM) architectures in
a distributed network of nodes, where each node employs an LSTM-based structure for …

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking
problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) …

Distributed flooding is a fundamental information sharing method to obtaining network
consensus via peer-to-peer communication. However, a unified consensus-oriented …

The particle filtering algorithm was introduced in the 1990s as a numerical solution to the
Bayesian estimation problem for nonlinear and non-Gaussian systems and has been …

Wireless sensor networks (WSNs) have become a popular technology for a broad range of
applications where the goal is to track and forecast the evolution of time-varying physical …

In the design process of an agent-based model the pattern chosen for the activation of the
agents is an important choice. Every model design must include-either explicitly or implicitly …

Distributed signal processing algorithms have become a hot topic during the past years. One
class of algorithms that have received special attention are particles filters (PFs). However …

混沌信号在本质上属于非线性非高斯信号, 它在无线传感器网络下的应用还涉及到信号量化问题
, 这使得混沌信号在此应用环境下的信号盲分离更为棘手. 针对此问题, 本文在容积卡尔曼粒子 …