Title 



From exponential analysis to Padé approximation and Tensor decomposition, in one and more dimensions


Author 





Abstract 



Exponential analysis in signal processing is essentially what is known as sparse interpolation in computer algebra. We show how exponential analysis from regularly spaced samples is reformulated as Padé approximation from approximation theory and tensor decomposition from multilinear algebra. The univariate situation is briefly recalled and discussed in Sect. 1. The new connections from approximation theory and tensor decomposition to the multivariate generalization are the subject of Sect. 2. These connections immediately allow for some generalization of the sampling scheme, not covered by the current multivariate theory. An interesting computational illustration of the above in blind source separation is presented in Sect. 3. 


Language 



English


Source (journal) 



Lecture notes in computer science.  Berlin, 1973, currens 

Source (book) 



CASC 2018 : Computer Algebra in Scientific Computing
Proceedings 20th International Workshop, CASC 2018, September 1721, 2018, Lille, France 

Source (series) 



Theoretical computer science and general issues ; 11077 

Publication 



Cham : Springer, 2018


ISBN 



9783319996387


Volume/pages 



(2018), p. 116130


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