IEICE TRANSACTIONS on Fundamentals
Weighted Minimization of Roundoff Noise and Pole Sensitivity Subject to l2-Scaling Constraints for State-Space Digital Filters
Summary :
This paper deals with the problem of minimizing roundoff noise and pole sensitivity simultaneously subject to l2-scaling constraints for state-space digital filters. A novel measure for evaluating roundoff noise and pole sensitivity is proposed, and an efficient technique for minimizing this measure by jointly optimizing state-space realization and error feedback is explored, namely, the constrained optimization problem at hand is converted into an unconstrained problem and then the resultant problem is solved by employing a quasi-Newton algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E102-A No.11 pp.1473-1480
- Publication Date
- 2019/11/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E102.A.1473
- Type of Manuscript
- PAPER
- Category
- Digital Signal Processing
Authors
Yoichi HINAMOTO
NIT Kagawa Colledge
Akimitsu DOI
Hiroshima Institute of Technology
Keyword
Latest Issue
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Yoichi HINAMOTO, Akimitsu DOI, "Weighted Minimization of Roundoff Noise and Pole Sensitivity Subject to l2-Scaling Constraints for State-Space Digital Filters" in IEICE TRANSACTIONS on Fundamentals,
vol. E102-A, no. 11, pp. 1473-1480, November 2019, doi: 10.1587/transfun.E102.A.1473.
Abstract: This paper deals with the problem of minimizing roundoff noise and pole sensitivity simultaneously subject to l2-scaling constraints for state-space digital filters. A novel measure for evaluating roundoff noise and pole sensitivity is proposed, and an efficient technique for minimizing this measure by jointly optimizing state-space realization and error feedback is explored, namely, the constrained optimization problem at hand is converted into an unconstrained problem and then the resultant problem is solved by employing a quasi-Newton algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E102.A.1473/_p
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@ARTICLE{e102-a_11_1473,
author={Yoichi HINAMOTO, Akimitsu DOI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Weighted Minimization of Roundoff Noise and Pole Sensitivity Subject to l2-Scaling Constraints for State-Space Digital Filters},
year={2019},
volume={E102-A},
number={11},
pages={1473-1480},
abstract={This paper deals with the problem of minimizing roundoff noise and pole sensitivity simultaneously subject to l2-scaling constraints for state-space digital filters. A novel measure for evaluating roundoff noise and pole sensitivity is proposed, and an efficient technique for minimizing this measure by jointly optimizing state-space realization and error feedback is explored, namely, the constrained optimization problem at hand is converted into an unconstrained problem and then the resultant problem is solved by employing a quasi-Newton algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.},
keywords={},
doi={10.1587/transfun.E102.A.1473},
ISSN={1745-1337},
month={November},}
Copy
TY - JOUR
TI - Weighted Minimization of Roundoff Noise and Pole Sensitivity Subject to l2-Scaling Constraints for State-Space Digital Filters
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1473
EP - 1480
AU - Yoichi HINAMOTO
AU - Akimitsu DOI
PY - 2019
DO - 10.1587/transfun.E102.A.1473
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E102-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2019
AB - This paper deals with the problem of minimizing roundoff noise and pole sensitivity simultaneously subject to l2-scaling constraints for state-space digital filters. A novel measure for evaluating roundoff noise and pole sensitivity is proposed, and an efficient technique for minimizing this measure by jointly optimizing state-space realization and error feedback is explored, namely, the constrained optimization problem at hand is converted into an unconstrained problem and then the resultant problem is solved by employing a quasi-Newton algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.
ER -
English
