Multilevel mixture Kalman filter
EURASIP Journal on Applied Signal Processing
Robust video stabilization based on particle filter tracking of projected camera motion
IEEE Transactions on Circuits and Systems for Video Technology
Adaptive sensor fault detection and identification using particle filter algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Nonlinear speech enhancement: an overview
Progress in nonlinear speech processing
Discrete cosine transform particle filter speech enhancement
Speech Communication
Particle filter enhancement of speech spectral amplitudes
IEEE Transactions on Audio, Speech, and Language Processing
Proceedings of the 4th ACM Multimedia Systems Conference
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We describe methods for applying Monte Carlo filtering and smoothing for estimation of unobserved states in a nonlinear state-space model. By exploiting the statistical structure of the model, we develop a Rao-Blackwellized particle smoother. Due to the lengthy nature of real signals, we suggest processing the data in blocks, and a block-based smoother algorithm is developed for this purpose. All the algorithms suggested are tested with real speech and audio data, and the results are shown and compared with those generated using the generic particle smoother and the extended Kalman filter (EKF). It is found that the proposed Rao-Blackwellized particle smoother improves on the standard particle smoother and the extended Kalman smoother. In addition, the proposed block-based smoother algorithm enhances the efficiency of the proposed Rao-Blackwellized smoother by significantly reducing the storage capacity required for the particle information