IEICE TRANSACTIONS on Communications
Time Shift Parameter Setting of Temporal Decorrelation Source Separation for Periodic Gaussian Signals
Summary :
Temporal Decorrelation source SEParation (TDSEP) is a blind separation scheme that utilizes the time structure of the source signals, typically, their periodicities. The advantage of TDSEP over non-Gaussianity based methods is that it can separate Gaussian signals as long as they are periodic. However, its shortcoming is that separation performance (SEP) heavily depends upon the values of the time shift parameters (TSPs). This paper proposes a method to automatically and blindly estimate a set of TSPs that achieves optimal SEP against periodic Gaussian signals. It is also shown that, selecting the same number of TSPs as that of the source signals, is sufficient to obtain optimal SEP, and adding more TSPs does not improve SEP, but only increases the computational complexity. The simulation example showed that the SEP is higher by approximately 20dB, compared with the ordinary method. It is also shown that the proposed method successfully selects just the same number of TSPs as that of incoming signals.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E96-B No.12 pp.3190-3198
- Publication Date
- 2013/12/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E96.B.3190
- Type of Manuscript
- PAPER
- Category
- Sensing
Authors
Takeshi AMISHIMA
Mitsubishi Electric Corporation
Kazufumi HIRATA
Mitsubishi Electric Corporation
Keyword
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Takeshi AMISHIMA, Kazufumi HIRATA, "Time Shift Parameter Setting of Temporal Decorrelation Source Separation for Periodic Gaussian Signals" in IEICE TRANSACTIONS on Communications,
vol. E96-B, no. 12, pp. 3190-3198, December 2013, doi: 10.1587/transcom.E96.B.3190.
Abstract: Temporal Decorrelation source SEParation (TDSEP) is a blind separation scheme that utilizes the time structure of the source signals, typically, their periodicities. The advantage of TDSEP over non-Gaussianity based methods is that it can separate Gaussian signals as long as they are periodic. However, its shortcoming is that separation performance (SEP) heavily depends upon the values of the time shift parameters (TSPs). This paper proposes a method to automatically and blindly estimate a set of TSPs that achieves optimal SEP against periodic Gaussian signals. It is also shown that, selecting the same number of TSPs as that of the source signals, is sufficient to obtain optimal SEP, and adding more TSPs does not improve SEP, but only increases the computational complexity. The simulation example showed that the SEP is higher by approximately 20dB, compared with the ordinary method. It is also shown that the proposed method successfully selects just the same number of TSPs as that of incoming signals.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E96.B.3190/_p
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@ARTICLE{e96-b_12_3190,
author={Takeshi AMISHIMA, Kazufumi HIRATA, },
journal={IEICE TRANSACTIONS on Communications},
title={Time Shift Parameter Setting of Temporal Decorrelation Source Separation for Periodic Gaussian Signals},
year={2013},
volume={E96-B},
number={12},
pages={3190-3198},
abstract={Temporal Decorrelation source SEParation (TDSEP) is a blind separation scheme that utilizes the time structure of the source signals, typically, their periodicities. The advantage of TDSEP over non-Gaussianity based methods is that it can separate Gaussian signals as long as they are periodic. However, its shortcoming is that separation performance (SEP) heavily depends upon the values of the time shift parameters (TSPs). This paper proposes a method to automatically and blindly estimate a set of TSPs that achieves optimal SEP against periodic Gaussian signals. It is also shown that, selecting the same number of TSPs as that of the source signals, is sufficient to obtain optimal SEP, and adding more TSPs does not improve SEP, but only increases the computational complexity. The simulation example showed that the SEP is higher by approximately 20dB, compared with the ordinary method. It is also shown that the proposed method successfully selects just the same number of TSPs as that of incoming signals.},
keywords={},
doi={10.1587/transcom.E96.B.3190},
ISSN={1745-1345},
month={December},}
Copy
TY - JOUR
TI - Time Shift Parameter Setting of Temporal Decorrelation Source Separation for Periodic Gaussian Signals
T2 - IEICE TRANSACTIONS on Communications
SP - 3190
EP - 3198
AU - Takeshi AMISHIMA
AU - Kazufumi HIRATA
PY - 2013
DO - 10.1587/transcom.E96.B.3190
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E96-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2013
AB - Temporal Decorrelation source SEParation (TDSEP) is a blind separation scheme that utilizes the time structure of the source signals, typically, their periodicities. The advantage of TDSEP over non-Gaussianity based methods is that it can separate Gaussian signals as long as they are periodic. However, its shortcoming is that separation performance (SEP) heavily depends upon the values of the time shift parameters (TSPs). This paper proposes a method to automatically and blindly estimate a set of TSPs that achieves optimal SEP against periodic Gaussian signals. It is also shown that, selecting the same number of TSPs as that of the source signals, is sufficient to obtain optimal SEP, and adding more TSPs does not improve SEP, but only increases the computational complexity. The simulation example showed that the SEP is higher by approximately 20dB, compared with the ordinary method. It is also shown that the proposed method successfully selects just the same number of TSPs as that of incoming signals.
ER -
English
