DocumentCode
3339635
Title
Monte Carlo smoothing for non-linearly distorted signals
Author
Fong, William ; Godsill, Simon
Author_Institution
Signal Process. Group, Cambridge Univ., UK
Volume
6
fYear
2001
fDate
2001
Firstpage
3997
Abstract
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
Keywords
Monte Carlo methods; audio signal processing; nonlinear distortion; quantisation (signal); smoothing methods; state estimation; Monte Carlo filtering; Monte Carlo smoothing; audio data; block-based smoother algorithm; de-quantisation; declipping; non-linearly distorted signals; unobserved state estimation; Distortion; Filtering; Monte Carlo methods; Nonlinear filters; Particle filters; Probability; Signal processing; Signal processing algorithms; Smoothing methods; State estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location
Salt Lake City, UT
ISSN
1520-6149
Print_ISBN
0-7803-7041-4
Type
conf
DOI
10.1109/ICASSP.2001.940720
Filename
940720
Link To Document