Title :
Monte Carlo smoothing for non-linearly distorted signals
Author :
Fong, William ; Godsill, Simon
Author_Institution :
Signal Process. Group, Cambridge Univ., UK
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
Print_ISBN :
0-7803-7041-4
DOI :
10.1109/ICASSP.2001.940720
