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Monte Carlo smoothing for non-linearly distorted signals

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2 Author(s)
Fong, William ; Signal Process. Group, Cambridge Univ., UK ; Godsill, S.

We develop methods for Monte Carlo filtering and smoothing for estimating an unobserved state given a non-linearly distorted signal. 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. In particular, we describe algorithms for de-quantisation and declipping in detail. Both algorithms are tested with real audio data which is either heavily quantised or clipped and the results are shown

Published in:

Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on  (Volume:6 )

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