Title :
Trellis-based search of the maximum a posteriori sequence using particle filtering
Author :
Bertozzi, Tanya ; Le Ruyet, Didier ; Rigal, Gilles ; Vu-Thien, Han
Author_Institution :
DIGINEXT, Aix En Provence, France
Abstract :
For a given computational complexity, the Viterbi algorithm applied on the discrete representation of the state space provided by a standard particle filtering, outperforms the particle filtering. However, the computational complexity of the Viterbi algorithm is still high. We propose to use the M and T algorithms in order to reduce the computational complexity of the Viterbi algorithm and we show that these algorithms enable a reduction of the number of particles by up to 20%, practically without loss of performance with respect to the Viterbi algorithm.
Keywords :
Monte Carlo methods; computational complexity; discrete systems; filtering theory; maximum likelihood estimation; nonlinear filters; search problems; state estimation; state-space methods; Viterbi algorithm; computational complexity; maximum a posteriori sequence; nonlinear filtering; particle filtering; sequential Monte Carlo methods; state estimation; trellis-based search; Computational complexity; Data analysis; Filtering; Mathematical model; Sensor phenomena and characterization; Sensor systems; State estimation; State-space methods; Viterbi algorithm; White noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Print_ISBN :
0-7803-7663-3
DOI :
10.1109/ICASSP.2003.1201776