TY - GEN
T1 - On lossy compression of binary matrices
AU - Bustin, Ronit
AU - Shayevitz, Ofer
N1 - Publisher Copyright: © 2017 IEEE.
PY - 2017/8/9
Y1 - 2017/8/9
N2 - We consider lossy compression of random binary matrices under distortion constraints that strive to preserve the structure of the matrix. Specifically, we assume that matrix elements are statistically independent (but not necessarily identically distributed), and that the worst case row/column average distortion is to be controlled. We discuss a natural notion of matrix types termed (R, c)-type, and provide various results concerning its probability and cardinality, as well as a 'Sanov-type' result, in the spirit of the method-of-types. We then derive bounds on the associated matrix ratedistortion function via a suitable matrix version of the covering lemma.
AB - We consider lossy compression of random binary matrices under distortion constraints that strive to preserve the structure of the matrix. Specifically, we assume that matrix elements are statistically independent (but not necessarily identically distributed), and that the worst case row/column average distortion is to be controlled. We discuss a natural notion of matrix types termed (R, c)-type, and provide various results concerning its probability and cardinality, as well as a 'Sanov-type' result, in the spirit of the method-of-types. We then derive bounds on the associated matrix ratedistortion function via a suitable matrix version of the covering lemma.
UR - http://www.scopus.com/inward/record.url?scp=85034039622&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2017.8006794
DO - 10.1109/ISIT.2017.8006794
M3 - منشور من مؤتمر
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 1573
EP - 1577
BT - 2017 IEEE International Symposium on Information Theory, ISIT 2017
T2 - 2017 IEEE International Symposium on Information Theory, ISIT 2017
Y2 - 25 June 2017 through 30 June 2017
ER -