• Structural Engineering and Mechanics
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• v.3 no.4
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• pp.373-382
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• 1995

The weighting strategy has received a great attention and has been widely applied to multicriterion optimization. This gaper examines a global criterion method (GCM) with the weighting objectives strategy in fuzzy structural engineering problems. Fuzziness of those problems are in their design goals, constraints and variables. Most of the constraints are originated from analysis of engineering mechanics. The GCM is verified to be equivalent to fuzzy goal programming via a truss design. Continued and mixed discrete variable spaces are presented and examined using a fuzzy global criterion method (FGCM). In the design process a weighting parameter with fuzzy information is introduced into the design and decision making. We use a uniform machine-tool spindle as an illustrative example in continuous design space. Fuzzy multicriterion optimization in mixed design space is illustrated by the design of mechanical spring stacks. Results show that weighting strategy in FGCM can generate both the best compromise solution and a set of Pareto solutions in fuzzy environment. Weighting technique with fuzziness provides a more relaxed design domain, which increases the satisfying degree of a compromise solution or improves the final design.

• Nuclear Engineering and Technology
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• v.30 no.4
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• pp.353-363
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• 1998

The H$_{\infty}$ algorithms of the mixed weight sensitivity is used for the robust design of the reactor power control system. The mixed weight sensitivity method requires the selection of the proper weighting functions for the loop shaping in frequency domain. The complexity of the system equation and the non-convexity of the problem make it very difficult to determine the weighting functions. The genetic algorithm which is improved and hybridized with the simulated annealing is applied to determine the weighting functions. This approach permits an automatic calculation and the resultant system shows good robustness and performance.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2E
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• pp.24-30
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• 1999

In this paper, we propose a weighting dependent mixed source model (WD-MSM) coder that is an improved version of a CELP-based mixed source model (C-MSM) coder. The coder classifies speech segments into three types : voiced, unvoiced and mixed. The excitation for a voiced frame is an adaptive source, and the excitation for an unvoiced frame is a stochastic source. The coder has a modified mixed source for a mixed frame. We apply different weighting functions for three classes. Simulation results show that the proposed coder at 4 kbits/s yields very good performance both subjectively and objectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.6
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• pp.37-44
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• 2018

This study proposed the modified weighting values for jointed rock slopes. The studies on deduction of evaluation index and calculation of weighting, development of criteria for evaluation and evaluation models have been conducted through decision making techniques such as the Delphi method and the AHP method by many researchers. Because these decisions making techniques may be less objective, it is necessary to calculate reasonable weighting considering both an objective weighting and a subjective weighting simultaneously. In this study, utilizing the inspection data of jointed rock slopes, an objective weighting that the concept of entropy is applied was calculated. And the subjective weighting values by AHP technique was calculated based on the opinion of experts. And a modified weighting was suggested by combining the two. As a result, it was found that jointed rock slopes have higher weighting in artificial factors and the damage status items. In addition based on the finally suggested weighting (mixed weighting), the revised evaluation criteria could be presented by converting it into the evaluation score (76 points). And it is expected that it could be usefully utilized upon inspections on cutting slopes and safety diagnosis since objective and highly reliable criteria compared to the condition evaluation criteria that are currently used could be presented through the results of the study.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.340-343
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• 1995

In this paper, we get a reduced order controller in $H^{\infty}$ mixed sensitivity problem with weighting functions. For this purpose, we define frequency weighted coprime factor of plant in $H^{\infty}$ mixed sensitivity problem and reduce the coprime factor using the frequency weighted balanced truncation technique. The we design the controller for plant with reduced order coprime factor using J-lossless coprime factorization technique. Using this approach, we can derive the robust stability condition and achieve good performance preservation in the closed loop system with reduced order controller. And it behaves well in both stable plant and unstable plant.t.

• Journal of IKEEE
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• v.20 no.2
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• pp.136-142
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• 2016

This paper presents a non-local means (NLM) denoising algorithm based on a new weighting function using a mixed norm. The fidelity of the difference between an anchor patch and the reference patch in the NLM denoising depends on noise level and local activity. This paper introduces a new weighting function based on a mixed norm type of which the order is determined by noise level and local activity of an anchor patch, so that the performance of the NLM denoising can be enhanced. Experimental results demonstrate the objective and subjective capability of the proposed algorithm. In addition, it was verified that the proposed algorithm can be used to improve the performance of the other $l_2$ norm based non-local means denoising algorithms

• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.193-197
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• 2004

In this paper, a combination problem of controllers which are the same type of $H_{\infty}$ controllers designed with different weighting functions. This approach can remove the difficulty in the selection of the weighting functions. As a sub-controller, the Youla type of $H_{\infty}$ controller is used. In the $H_{\infty}$ controller, Youla parameterization is used to minimize $H_{\infty}$ norm of mixed sensitivity function by using polynomial approach. Computer simulation results show the robustness improvement and the performance improvement.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.713-718
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• 2016

Predicting precise specifications of differential mixed-signal circuits is a difficult problem, because analytically derived correlation between process variations and conventional specifications exhibits the limited prediction accuracy due to the phase unbalance, for most self-tests. This paper proposes an efficient prediction technique to provide accurate specifications of differential mixed-signal circuits in a system-on-chip (SoC) based on a nonlinear statistical nonlinear regression technique. A spectrally pure sinusoidal signal is applied to a differential DUT, and its output is fed into another differential DUT through a weighting circuitry in the loopback configuration. The weighting circuitry, which is employed from the previous work [3], efficiently produces different weights on the harmonics of the loopback responses, i.e., the signatures. The correlation models, which map the signatures to the conventional specifications, are built based on the statistical nonlinear regression technique, in order to predict accurate nonlinearities of individual DUTs. In production testing, once the efficient signatures are measured, and plugged into the obtained correlation models, the harmonic coefficients of DUTs are readily identified. This work provides a practical test solution to overcome the serious test issue of differential mixed-signal circuits; the low accuracy of analytically derived model is much lower by the errors from the unbalance. Hardware measurement results showed less than 1.0 dB of the prediction error, validating that this approach can be used as production test.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.410-415
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• 2005

Recently, most of the speaker verification systems are based on the pattern recognition approach method. And performance of the pattern-classifier depends on how to classify a variety of speakers' feature parameters. In order to classify feature parameters efficiently and effectively, it is of great importance to enlarge variations between speakers and effectively measure distances between feature parameters. Therefore, this paper would suggest the positively mixed model scheme that can enlarge inter-speaker variation by searching the individual model with world model at the same time. During decision procedure, we can maximize inter-speaker variation by using the proposed mixed model scheme. We also make use of a symbol probability weighting function in this system so as to reduce vector quantization errors by measuring symbol probability derived from the distance rate of between the world codebook and individual codebook. As the result of our experiment using this method, we could halve the Detection Cost Function (DCF) of the system from $2.37\%\;to\;1.16\%$.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.888-891
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• 1996

The objective of a mixed H$_{2}$/H$_{\infty}$ controller of active suspension system is to achieve not only the general performance improvement(H$_{2}$) but also the worst case disturbance rejection(H$_{\infty}$). In this paper, a mixed H$_{2}$/H$_{\infty}$ controller for an active suspension system, comparing the performance with that of an H$_{2}$ controller and of an H$_{\infty}$ controller.ler.EX> controller.