Title : 
Blind separation of three binary sources from one nonlinear mixture
         
        
            Author : 
Diamantaras, Konstantinos I. ; Papadimitriou, Theophilos
         
        
            Author_Institution : 
Dept. of Inf., TEI of Thessaloniki, Sindos, Greece
         
        
        
            fDate : 
Aug. 29 2010-Sept. 1 2010
         
        
        
        
            Abstract : 
This paper presents a blind method for the separation of three binary sources from a single, nonlinear mixture. Since the problem is intractable, in general, we focus on the special case where the nonlinearity is an odd function. The proposed method is based on clustering of the observed data and the geometry of the cluster centers. The separation algorithm is analytical, it does not involve iterative optimization and it is computationally efficient since it involves the inversion of a small matrix. Due to the structure of the problem, the true sources are extracted together with spurious signals adding one more indeterminacy to the usual sign and order indeterminacy of the sources. However, in some applications, eg. the separation of binary images, this indeterminacy can be resolved by visual inspection.
         
        
            Keywords : 
blind source separation; image processing; signal reconstruction; binary images; binary sources; blind separation; nonlinear mixture; visual inspection; Artificial neural networks;
         
        
        
        
            Conference_Titel : 
Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on
         
        
            Conference_Location : 
Kittila
         
        
        
            Print_ISBN : 
978-1-4244-7875-0
         
        
            Electronic_ISBN : 
1551-2541
         
        
        
            DOI : 
10.1109/MLSP.2010.5589211