bibtype |
J -
Journal Article
|
ARLID |
0391438 |
utime |
20240111140829.4 |
mtime |
20130404235959.9 |
WOS |
000317398500010 |
SCOPUS |
84875651157 |
DOI |
10.1109/TSP.2013.2245660 |
title
(primary) (eng) |
Cramér-Rao-Induced Bounds for CANDECOMP/ PARAFAC Tensor Decomposition |
specification |
page_count |
12 s. |
media_type |
P |
|
serial |
ARLID |
cav_un_epca*0256727 |
ISSN |
1053-587X |
title
|
IEEE Transactions on Signal Processing |
volume_id |
61 |
volume |
8 (2013) |
page_num |
1986-1997 |
|
keyword |
Canonical polyadic decomposition |
keyword |
multilinear models |
keyword |
stability |
author
(primary) |
ARLID |
cav_un_auth*0101212 |
name1 |
Tichavský |
name2 |
Petr |
full_dept (cz) |
Stochastická informatika |
full_dept (eng) |
Department of Stochastic Informatics |
department (cz) |
SI |
department (eng) |
SI |
institution |
UTIA-B |
full_dept |
Department of Stochastic Informatics |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0274170 |
name1 |
Phan |
name2 |
A. H. |
country |
JP |
|
author
|
ARLID |
cav_un_auth*0108100 |
name1 |
Koldovský |
name2 |
Zbyněk |
full_dept (cz) |
Stochastická informatika |
full_dept |
Department of Stochastic Informatics |
department (cz) |
SI |
department |
SI |
institution |
UTIA-B |
full_dept |
Department of Stochastic Informatics |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
source |
|
cas_special |
project |
project_id |
GA102/09/1278 |
agency |
GA ČR |
ARLID |
cav_un_auth*0253174 |
|
project |
project_id |
GAP103/11/1947 |
agency |
GA ČR |
country |
CZ |
ARLID |
cav_un_auth*0301478 |
|
abstract
(eng) |
This paper presents a Cramér-Rao lower bound (CRLB) on the variance of unbiased estimates of factor matrices in Canonical Polyadic (CP) or CANDECOMP/PARAFAC (CP) decompositions of a tensor from noisy observations, (i.e., the tensor plus a random Gaussian-distributed tensor). A novel expression is derived for a bound on the mean square angular error of factors along a selected dimension of a tensor of an arbitrary dimension. Insightful expressions are derived for tensors of rank 1 and rank 2 of arbitrary dimension and for tensors of arbitrary dimension and rank, where two factor matrices have orthogonal columns. The results can be used as a gauge of performance of different approximate CP decomposition algorithms, prediction of their accuracy, and for checking stability of a given decomposition of a tensor (condition whether the CRLB is finite or not). |
reportyear |
2014 |
RIV |
BB |
num_of_auth |
3 |
mrcbC52 |
4 A 4a 20231122135558.1 |
inst_support |
RVO:67985556 |
permalink |
http://hdl.handle.net/11104/0220515 |
mrcbT16-e |
ENGINEERINGELECTRICALELECTRONIC |
mrcbT16-f |
3.592 |
mrcbT16-g |
0.439 |
mrcbT16-h |
7.II |
mrcbT16-i |
0.07199 |
mrcbT16-j |
1.62 |
mrcbT16-k |
22913 |
mrcbT16-l |
508 |
mrcbT16-s |
2.074 |
mrcbT16-4 |
Q1 |
mrcbT16-B |
94.605 |
mrcbT16-C |
90.927 |
mrcbT16-D |
Q1* |
mrcbT16-E |
Q1* |
arlyear |
2013 |
mrcbTft |
\nSoubory v repozitáři: tichavsky-0391438.pdf |
mrcbU14 |
84875651157 SCOPUS |
mrcbU34 |
000317398500010 WOS |
mrcbU56 |
3MB |
mrcbU63 |
cav_un_epca*0256727 IEEE Transactions on Signal Processing 1053-587X 1941-0476 Roč. 61 č. 8 2013 1986 1997 |
|