A holistic comparison of the different resampling algorithms for particle filter based prognosis using lithium ion batteries as a case study
K Pugalenthi, N Raghavan - Microelectronics Reliability, 2018 - Elsevier
Prognostic health management (PHM) is a critical and essential aspect of any robust
maintenance program in the manufacturing industry for early failure detection and prediction …
maintenance program in the manufacturing industry for early failure detection and prediction …
Improved distributed particle filters for tracking in a wireless sensor network
A novel distributed particle filter algorithm is presented, called drift homotopy likelihood
bridging particle filter (DHLB-PF). The DHLB-PF is designed to surmount the degeneracy …
bridging particle filter (DHLB-PF). The DHLB-PF is designed to surmount the degeneracy …
Distributed robust Bayesian filtering for state estimation
We study the problem of distributed filtering for state space models over networks, which
aims to collaboratively estimate the states by a network of nodes. Most of existing works on …
aims to collaboratively estimate the states by a network of nodes. Most of existing works on …
Distributed estimation using particles intersection
A technique is presented for combining arbitrary empirical probability density estimates
whose interdependencies are unspecified. The underlying estimates may be, for example …
whose interdependencies are unspecified. The underlying estimates may be, for example …
Distributed bayesian filter using measurement dissemination for multiple unmanned ground vehicles with dynamically changing interaction topologies
This paper presents a novel distributed Bayesian filtering (DBF) method using measurement
dissemination (MD) for multiple unmanned ground vehicles (UGVs) with dynamically …
dissemination (MD) for multiple unmanned ground vehicles (UGVs) with dynamically …
Information fusion using particles intersection
A technique is presented for combining arbitrary empirical probability density estimates
whose interdependencies are unspecified. The underlying estimates may be, for example …
whose interdependencies are unspecified. The underlying estimates may be, for example …
Distributed Kalman and particle filtering
AH Sayed, PM Djurić, F Hlawatsch - Cooperative and Graph Signal …, 2018 - Elsevier
This chapter discusses distributed Kalman and particle filtering algorithms for state
estimation in decentralized multiagent networks. It is assumed that the spatially distributed …
estimation in decentralized multiagent networks. It is assumed that the spatially distributed …
[图书][B] Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing
Signals and Images: Advances and Results in Speech, Estimation, Compression,
Recognition, Filtering, and Processing cohesively combines contributions from field experts …
Recognition, Filtering, and Processing cohesively combines contributions from field experts …
Particle filter based target tracking in wireless sensor networks using support vector machine
AA Rezaee, A Namazi Nik - Computer and Knowledge Engineering, 2018 - cke.um.ac.ir
Target tracking is estimating the state of moving targets using noisy measurements obtained
at a single observation point or node. Particle filters or sequential Monte Carlo methods use …
at a single observation point or node. Particle filters or sequential Monte Carlo methods use …
[引用][C] A modified particle filter algorithm and its implementation on a wireless ZigBee network based navigation system
M Aykaç - platform.almanhal.com
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