Gaussian sum particle filtering

By Jayesh H. Kotecha, Petar M. Djuric. IEEE Transactions on Signal Processing, 2003

525 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/04561f6c6ea511cfa71c5225b288406886900f04

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Fredrik K. Gustafsson
2. Petar M. Djuric
3. Jayesh H. Kotecha
4. Thomas Bo Schön
5. Qasim M. Chaudhari
6. Erchin Serpedin
7. Yik-Chung Wu
8. Simon Timothy O'Callaghan

In Control and Systems Engineering

1. Fredrik K. Gustafsson
2. Qasim M. Chaudhari
3. Erchin Serpedin
4. Yik-Chung Wu
5. Jayesh H. Kotecha
6. Petar M. Djuric
7. Thomas Bo Schön
8. Fredrik Lindsten

Citations in the corpus

• Clock Synchronization of Wireless Sensor Networks (2011, methodology): “This solution presents a smaller computational complexity than a pure particle filter solution, as the procedure called resampling is avoided [40].”
• Multi-modal estimation with kernel embeddings for learning motion models (2013, background): “Gaussian sum filters relax this restriction to representation as a Gaussian sum [17] but suffer from mixture component impoverishment.”
• Gaussian particle filtering (2001, methodology): “An example of the above is given in a companion paper [24],”
• Marginalized particle filters for mixed linear/nonlinear state-space models (2005, background): “, the auxiliary particle filter [34] and the Gaussian particle filter [26], [27].”
• Particle filter theory and practice with positioning applications (2010, methodology): “The Gaussian sum particle filter (GSPF) i n [45] uses a Gaussian sum instead.”