Real time noise-cancellation using ICA, PSO and PE
Date
2012Source Title
2012 20th Signal Processing and Communications Applications Conference (SIU)
Print ISSN
2165-0608
Publisher
IEEE
Language
Turkish
Type
Conference PaperItem Usage Stats
220
views
views
153
downloads
downloads
Abstract
In order to provide noiseless transmission of speech in wireless communication systems a real-time implementable noise cancellation algorithm is developed. Speech and noise sources are not known but only their mixtures are observed. That system is modeled with instantaneous mixture model. Combination of independent component analysis (ICA) and particle swarm optimization (PSO) algorithms is used to separate speech and noise. However, ICA has an ambiguity such that it is not possible to know which one of the separated signals is speech or noise. As a result, the transmitted signal can be noise, instead of speech. To overcome this ambiguity problem, a pitch extraction (PE) algorithm is developed and combined with ICA-PSO. ICAPSO-PE algorithm is implemented in MATLAB. Contributions of this work are modifying objective functions of ICA algorithm to make them more robust, combining ICA with PSO to make it work fast and robust, and overcoming the ambiguity problem using PE algorithm. © 2012 IEEE.
Keywords
ICA algorithmsInstantaneous mixtures
Noise source
Noise-cancellation algorithms
Objective functions
Particle swarm optimization algorithm
Pitch extraction
Real time
Transmitted signal
Wireless communication system
Algorithms
Independent component analysis
Particle swarm optimization (PSO)
Separation
Signal processing
Speech communication
Speech transmission