Abstract :
The ALS algorithm, used to fit the PARAFAC model, sometimes needs a large number of iterations before converging. The slowness in convergence can be due to the large size of the data, or to the presence of degeneracies, etc. Several methods have been proposed to speed up the algorithm, some of which are compression (R. Bro and C.A. Andersson, 1998), and line search (R. Bro, 1998). In M. Rajih and P. Comon (2005) presents a novel method for speeding up the algorithm, enhanced line search (ELS), that shows better results in simulations compared to the existing methods, especially in the case of degeneracy. This paper gives an application of ELS to blindly identify the mixing matrix of an under-determined mixture (UDM): algorithm ALESCAF, and states the identifiability conditions based on ALESCAF
Keywords :
channel allocation; matrix algebra; search problems; ALESCAF; PARAFAC model; blind channel identification; enhanced line search; identifiability conditions; under-determined mixture; Argon; Convergence; Laboratories; Least squares methods; Matrix decomposition; Principal component analysis; Psychometric testing; Signal processing algorithms; Singular value decomposition; Tensile stress;
