Analyzing data into quantized components

Author

Diamantaras, Konstantinos ; Papadimitriou, Theophilos ; Goulianas, Konstantinos

Author_Institution

Dept. of Inf. Technol., Technol. Educ. Inst. of Thessaloniki, Sindos, Greece

fYear

2014

fDate

4-9 May 2014

Firstpage

6211

Lastpage

6215

Abstract

Signals in various applications are often generated by linear combinations of quantized components. The analysis of data into such components is treated here as a matrix analysis problem. We first show that the component alphabet can always be normalized to the levels 0, ..., M-1, without loss of generality. Then we study certain conditions under which the decomposition is possible. In particular, we present an analytical algorithm based on the differences of the observed points and the recursive estimation of the quantized components when the number of unique observed points is sufficiently large.

Keywords

blind source separation; data analysis; matrix decomposition; quantisation (signal); recursive estimation; analytical algorithm; component alphabet; data analysis; linear combinations; matrix analysis problem; quantized components; recursive estimation; Algorithm design and analysis; DH-HEMTs; Manganese; Matrix decomposition; Principal component analysis; Silicon; Vectors; blind source separation; data analysis; matrix factorization; quantized components;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on

Conference_Location

Florence

Type

conf

DOI

10.1109/ICASSP.2014.6854798

Filename

6854798