The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 폐쇄형 솔루션을 제안한다. L2-감도 최소화 대상 L2-실제 극점을 갖는 2차 상태공간 디지털 필터에 대한 스케일링 제약. 2차 디지털 필터의 두 가지 경우, 즉 개별 실제 극점과 다중 실제 극점을 고려합니다. 제안된 접근법은 적절한 변수 변환을 통해 제한된 최적화 문제를 비제약 최적화 문제로 줄입니다. 우리는 다음을 표현할 수 있습니다. L2-지수 함수의 간단한 선형 조합으로 감도를 계산하고 L2-간단한 다항식을 이용한 민감도 최소화 문제. 결과적으로, L2- 민감도는 닫힌 형태로 표현되며, 민감도는 최소화됩니다. L2-반복적인 계산 없이 확장 제약 조건이 달성됩니다.
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부
Shunsuke YAMAKI, Masahide ABE, Masayuki KAWAMATA, "Closed Form Solutions to L2-Sensitivity Minimization Subject to L2-Scaling Constraints for Second-Order State-Space Digital Filters with Real Poles" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 2, pp. 476-487, February 2010, doi: 10.1587/transfun.E93.A.476.
Abstract: This paper proposes closed form solutions to the L2-sensitivity minimization subject to L2-scaling constraints for second-order state-space digital filters with real poles. We consider two cases of second-order digital filters: distinct real poles and multiple real poles. The proposed approach reduces the constrained optimization problem to an unconstrained optimization problem by appropriate variable transformation. We can express the L2-sensitivity by a simple linear combination of exponential functions and formulate the L2-sensitivity minimization problem by a simple polynomial equation. As a result, L2-sensitivity is expressed in closed form, and its minimization subject to L2-scaling constraints is achieved without iterative calculations.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.476/_p
부
@ARTICLE{e93-a_2_476,
author={Shunsuke YAMAKI, Masahide ABE, Masayuki KAWAMATA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Closed Form Solutions to L2-Sensitivity Minimization Subject to L2-Scaling Constraints for Second-Order State-Space Digital Filters with Real Poles},
year={2010},
volume={E93-A},
number={2},
pages={476-487},
abstract={This paper proposes closed form solutions to the L2-sensitivity minimization subject to L2-scaling constraints for second-order state-space digital filters with real poles. We consider two cases of second-order digital filters: distinct real poles and multiple real poles. The proposed approach reduces the constrained optimization problem to an unconstrained optimization problem by appropriate variable transformation. We can express the L2-sensitivity by a simple linear combination of exponential functions and formulate the L2-sensitivity minimization problem by a simple polynomial equation. As a result, L2-sensitivity is expressed in closed form, and its minimization subject to L2-scaling constraints is achieved without iterative calculations.},
keywords={},
doi={10.1587/transfun.E93.A.476},
ISSN={1745-1337},
month={February},}
부
TY - JOUR
TI - Closed Form Solutions to L2-Sensitivity Minimization Subject to L2-Scaling Constraints for Second-Order State-Space Digital Filters with Real Poles
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 476
EP - 487
AU - Shunsuke YAMAKI
AU - Masahide ABE
AU - Masayuki KAWAMATA
PY - 2010
DO - 10.1587/transfun.E93.A.476
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2010
AB - This paper proposes closed form solutions to the L2-sensitivity minimization subject to L2-scaling constraints for second-order state-space digital filters with real poles. We consider two cases of second-order digital filters: distinct real poles and multiple real poles. The proposed approach reduces the constrained optimization problem to an unconstrained optimization problem by appropriate variable transformation. We can express the L2-sensitivity by a simple linear combination of exponential functions and formulate the L2-sensitivity minimization problem by a simple polynomial equation. As a result, L2-sensitivity is expressed in closed form, and its minimization subject to L2-scaling constraints is achieved without iterative calculations.
ER -