IEICE TRANSACTIONS on Fundamentals
Digital Signal Processing Using Fuzzy Clustering
Summary :
A novel digital signal processing technique fuzzy filtering is proposed for estimating nonstationary signals with ambiguous changes, which are contaminated by additive white Gaussian noises. In this filter, fuzzy clustering is utilized for classifying signal components into groups in which the signal characteristics are considered to be similar. Since the boundary between the signal groups is ambiguous, the fuzzy clustering produces a better effect than crisp clustering. Moreover, robust characteristics are obtained for various values of the parameters and types of processed signals. Computer simulations successfully demonstrate its superior capability of filtering.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E74-A No.11 pp.3554-3558
- Publication Date
- 1991/11/25
- Publicized
- Online ISSN
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- Type of Manuscript
- Special Section PAPER (Special Issue on HAKONE Digital Signal Processing Symposium)
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Kaoru ARAKAWA, Yasuhiko ARAKAWA, "Digital Signal Processing Using Fuzzy Clustering" in IEICE TRANSACTIONS on Fundamentals,
vol. E74-A, no. 11, pp. 3554-3558, November 1991, doi: .
Abstract: A novel digital signal processing technique fuzzy filtering is proposed for estimating nonstationary signals with ambiguous changes, which are contaminated by additive white Gaussian noises. In this filter, fuzzy clustering is utilized for classifying signal components into groups in which the signal characteristics are considered to be similar. Since the boundary between the signal groups is ambiguous, the fuzzy clustering produces a better effect than crisp clustering. Moreover, robust characteristics are obtained for various values of the parameters and types of processed signals. Computer simulations successfully demonstrate its superior capability of filtering.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e74-a_11_3554/_p
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@ARTICLE{e74-a_11_3554,
author={Kaoru ARAKAWA, Yasuhiko ARAKAWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Digital Signal Processing Using Fuzzy Clustering},
year={1991},
volume={E74-A},
number={11},
pages={3554-3558},
abstract={A novel digital signal processing technique fuzzy filtering is proposed for estimating nonstationary signals with ambiguous changes, which are contaminated by additive white Gaussian noises. In this filter, fuzzy clustering is utilized for classifying signal components into groups in which the signal characteristics are considered to be similar. Since the boundary between the signal groups is ambiguous, the fuzzy clustering produces a better effect than crisp clustering. Moreover, robust characteristics are obtained for various values of the parameters and types of processed signals. Computer simulations successfully demonstrate its superior capability of filtering.},
keywords={},
doi={},
ISSN={},
month={November},}
Copy
TY - JOUR
TI - Digital Signal Processing Using Fuzzy Clustering
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3554
EP - 3558
AU - Kaoru ARAKAWA
AU - Yasuhiko ARAKAWA
PY - 1991
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E74-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 1991
AB - A novel digital signal processing technique fuzzy filtering is proposed for estimating nonstationary signals with ambiguous changes, which are contaminated by additive white Gaussian noises. In this filter, fuzzy clustering is utilized for classifying signal components into groups in which the signal characteristics are considered to be similar. Since the boundary between the signal groups is ambiguous, the fuzzy clustering produces a better effect than crisp clustering. Moreover, robust characteristics are obtained for various values of the parameters and types of processed signals. Computer simulations successfully demonstrate its superior capability of filtering.
ER -
English
