• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3559-3571
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• 2015

This paper addresses the problem of signal acquisition with a sparse representation in a given orthonormal basis using fewer noisy measurements. The authors formulate the problem statement for randomly measuring with strong signal noise. The impact of white Gaussian signals noise on the recovery performance is analyzed to provide a theoretical basis for the reasonable design of the measurement matrix. With the idea that the measurement matrix can be adapted for noise suppression in the adaptive CS system, an adapted selective compressive sensing (ASCS) scheme is proposed whose measurement matrix can be updated according to the noise information fed back by the processing center. In terms of objective recovery quality, failure rate and mean-square error (MSE), a comparison is made with some nonadaptive methods and existing CS measurement approaches. Extensive numerical experiments show that the proposed scheme has better noise suppression performance and improves the support recovery of sparse signal. The proposed scheme should have a great potential and bright prospect of broadband signals such as biological signal measurement and radar signal detection.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 정기총회 및 창립40주년기념 학술대회 학회본부
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• pp.133-136
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• 1987

This paper presents a new algorithm of optimal measurement system by using band matrix characteristic respectively for state estimation. A performance index of measurement system is established to reflect relation among measurement sets, probability of measurement failure and cost of individual meter installation. Selection ranking in the candidates of measurement sets is composed to guarantee the observability for any any single meter outage. Performance index sensitivity is introduced and recursive formula which based on the matrix inversion lemma used for selection. The proposed algorithm is composed of successive addition algorithm, successive elimination algorithm and combinatorial algorithm. The band matrix characteristic could save in memory requirements and calculate the performance index faster than earlier.

• 제어로봇시스템학회논문지
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• 제20권6호
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• pp.631-634
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• 2014

We propose a measurement state feedback controller for a class of nonlinear systems that have uncertain nonlinearity and sensor noise. The new design method based on the matrix inequality approach solves the measurement feedback control problem of a class of nonlinear systems. As a result, the proposed methods using a matrix inequality approach has the flexibility to apply the controller. In addition, the sensor noise can be attenuated for more generalized systems containing uncertain nonlinearities.

• 한국산업융합학회 논문집
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• 제21권2호
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• pp.63-70
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• 2018

In this paper, the design of a novel 6-axis compliance device with force/torque sensing capability and the experiment results on force measurement are presented. Unlike the traditional control methods using a force/torque sensor with very limited compliance, the force control method employs a compliant device to provide sufficient compliance between an industrial robot and a rigid environment for more stable force control. The proposed compliance device is designed to have a diagonal stiffness matrix at the tip and uses strain gauge measurement which is robust to dust and oil. The measurement circuit is designed with low-cost IC chips however the force resolution is 0.04N.

• 대한기계학회논문집A
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• 제26권6호
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• pp.1114-1119
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• 2002

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on 12-norm of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters for small order systems. In designing Kalman filters, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.313-318
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• 2001

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on $L_2-norm$ of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters. In designing Kalman filters for small order systems, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• 한국음향학회지
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• 제18권8호
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• pp.61-67
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• 1999

본 논문에서는 선형배열을 이용하여 음향을 측정하기 위한 새로운 빔형성 알고리듬을 제안한다. 제안 알고리듬은, FIR 필터 설계기법에 의해 가중상수 및 원하는 빔패턴을 설정하고 이를 초기치로 사용하여 원하는 빔패턴과의 오차가 최소가 되도록 가중상수를 최적화시킨다. 전 주파수에서의 지향지수 균일성 유지를 위해 옥타브대역을 부대역으로 세분하고 의사역행렬에 의해 전달행렬을 정방행렬화하여 각 부대역별로 최적화를 수행한다. 시뮬레이션 결과 제안 알고리듬이 선형배열에서 음향측정에 적합한 빔패턴 및 지향지수를 형성시켜 음향측정에 유용함을 확인하였다.

• International Journal of Quality Innovation
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• 제4권2호
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• pp.101-122
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• 2003

With the development of the American Customer satisfaction index (ACSI), research on customer satisfaction measurement or evaluation methods have become significant in the last decade. Most of international customer satisfaction barometers or indices are evolved based on the cause and effect relationship model of ACSI. Of critical importance to validity of customer satisfaction indices is how to construct a measurement attribute or indicator model and provide an effective implementation method effectively. Quality Function Deployment (QFD) is a very useful tool for translating the customer voice into product design through quality engineering. In fact, this is a methodology for measuring and analyzing evaluation indicators by their relationship matrix. In this paper, we will make an effort to integrate the framework of QFD into the measurement problem of customer satisfaction, and also develop a new multi-phase QFD model for evaluation of Customer Satisfaction Index (CSI). From the houses of quality in this model, the evaluation indicators impacting on customer's global satisfaction are identified by means of their relationship matrix. Then the evaluation indicator hierarchy and its measurement method for the customer satisfaction index are presented graphically. Furthermore, survey data from the Chinese automobile maintenance sector and a relevant case study are utilized to show the implementation method of the QFD model used to measure and analyze of customer satisfaction.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.129-132
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• 1999

This paper deals with the optimal filtering problem constrained to input noise signal corrupting the measurement output for linear discrete-time systems. The transfer matrix H$_2$and/or H$_{\infty}$ norms are used as criteria in an estimation error sense. In this paper, the mixed $H_2/H_{\infty}$ filtering Problem in lineal discrete-time systems is solved using the LMI approach, yielding a compromise between the H$_2$and H$_{\infty}$ filter designs. This filter design problems we formulated in a convex optimization framework using linear matrix inequalities. A numerical example is presented.

• 디지털산업정보학회논문지
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• 제9권1호
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• pp.111-118
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• 2013

This paper presents implementation of Air protocol analyzer and physical layer design algorithm. The analyzer is a measurement system providing real-time analysis of wireless signals between User Equipment (UE) and Node-B. The implemented system proposed in this paper consists of Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The waveform of Wideband Code Division Multiple Access (WCDMA) has been selected for verification of the proposed system. We designed the analyzer using equalizer algorithm and rake-receiver algorithm. Among various algorithms of designing the equalizer, we have chosen Linear Minimum Mean Square Error (LMMSE) equalizer that uses the inverse of channel matrix. Since the LMMSE equalizer uses the inverse channel matrix, it suffers from a large amount of computational load, while it outperforms most conventional equalizers. In this paper, we introduce an efficient procedure of reducing the computational load required by LMMSE equalizer-based receiver.