• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.3
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• pp.404-416
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• 2015

Small-area, low-power coarse and fine frequency detectors (FDs) are proposed for an adaptive bandwidth referenceless CDR with a wide range of input data rate. The coarse FD implemented with two flip-flops eliminates harmonic locking as long as the initial frequency of the CDR is lower than the target frequency. The fine FD samples the incoming input data by using half-rate four phase clocks, while the conventional rotational FD samples the full-rate clock signal by the incoming input data. The fine FD uses only a half number of flip-flops compared to the rotational FD by sharing the sampling and retiming circuitry with PLL. The proposed CDR chip in a 65-nm CMOS process satisfies the jitter tolerance specifications of both USB 3.0 and USB 3.1. The proposed CDR works in the range of input data rate; 2 Gb/s ~ 8 Gb/s at 1.2 V, 4 Gb/s ~ 11 Gb/s at 1.5 V. It consumes 26 mW at 5 Gb/s and 1.2 V, and 41 mW at 10 Gb/s and 1.5 V. The measured phase noise was -97.76 dBc/Hz at the 1 MHz frequency offset from the center frequency of 2.5 GHz. The measured rms jitter was 5.0 ps at 5 Gb/s and 4.5 ps at 10 Gb/s.

• Smart Structures and Systems
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• v.32 no.1
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• pp.9-21
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• 2023

The parameters of civil engineering structures have time-variant characteristics during their service. When extremely large external excitations, such as earthquake excitation to buildings or overweight vehicles to bridges, apply to structures, sudden or gradual damage may be caused. It is crucially necessary to detect the occurrence time and severity of the damage. The unscented Kalman filter (UKF), as one efficient estimator, is usually used to conduct the recursive identification of parameters. However, the conventional UKF algorithm has a weak tracking ability for time-variant structural parameters. To improve the identification ability of time-variant parameters, an adaptive UKF with forgetting factor (AUKF-FF) algorithm, in which the state covariance, innovation covariance and cross covariance are updated simultaneously with the help of the forgetting factor, is proposed. To verify the effectiveness of the method, this paper conducted two case studies as follows: the identification of time-variant parameters of a simply supported bridge when the vehicle passing, and the model updating of a six-story concrete frame structure with field test during the Yangbi earthquake excitation in Yunnan Province, China. The comparison results of the numerical studies show that the proposed method is superior to the conventional UKF algorithm for the time-variant parameter identification in convergence speed, accuracy and adaptability to the sampling frequency. The field test studies demonstrate that the proposed method can provide suggestions for solving practical problems.

• International journal of advanced smart convergence
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• v.3 no.2
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• pp.18-21
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• 2014

A control application requirements currently used is very low, such as packet loss rate, minimum delay on sensor networks with quality of service (QoS) requirements some packet delivery guarantee. This paper is the sampling period at the end of the actuator and sensor data transfer related to the Miss ratio for each source sensor node, use the controller and the internal ANFIS. The proposed scheme has the advantages of simplicity, scalability, and General. Simulation results of the proposed scheme can provide QoS support in WSANs.

• Speech Sciences
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• v.9 no.3
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• pp.17-24
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• 2002

The goal of this research is the real-time implementation of an AEC (Acoustic Echo Canceller) using the floating-point digital signal processor of TMS320C31. We employ an FIR-type adaptive filter with the conventional NLMS (Normalized Least Mean Square) algorithm for the adaptation of filter coefficients. We program and optimize the system in the assembler level to make it run in real-time. With 8 kHz sampling rate, the implemented AEC requires $46\;\mu$sec and $77\;\mu$sec computational time per sample for 128-and 256-tap filter, respectively. It corresponds to 37% and 62% of maximum computational ability of TMS320C31 DSP.

• Journal of the korean society of oceanography
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• v.32 no.1
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• pp.38-45
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• 1997

To find out the changes in vertical distribution patterns over the 24-h period, a key and the first step to tackle the problem of adaptive significance of diel vertical migration (DVM), vertically stratified time series samplings with multiple opening/closing plankton samplers were done in the East Sea of Korea (Sea of Japan). Sampling was done almost every 4 h for one day period following the same water parcel in Nov. 1995 and May 1996, respectively. Resultant patterns of vertical distribution showed that some species such as most abundant taxa Metridia pacifica and Scolecithyicella minor, both Copepoda, performed DVM even in the study area of strong thermal stratification. Their patterns of DVM such as distance scales and timing of movements were not the same each other, and they were separated from other taxa in the dendrogram obtained by the cluster analyses, Most minor taxa grouped in one, however, seemed not to do DVM in the study area of strong thermal stratification. They usually preferred the warmer surface layer where the foods were probably more abundant.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.550-553
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• 2005

To acquire radar target signature, various kinds of target are necessary. Measurement is one of the data acquiring method, but much time and high cost is required to get the target data from the real targets. Even if we can afford that, the targets we can access are very limited. To obtain target signatures avoiding these problems, we build the target CAD (Computer Aided Design) model for the calculation of target signatures. To speed up RCS calculation, we applied adaptive super-sampling and tested quite complex tank CAD model which is 1.4 hundred of thousands facet. We use calculated RCS data for ID range profile and 2D ISAR (Inverse Synthetic Aperture Radar) image formation. We adopted IFFT (Inverse Fast Fourier Transform) algorithm combined with polar formatting algorithm for the ISAR imaging. We could confirm the possibility of the construction of database from the images of CAD models for target classification applications.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.699-702
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• 1991

A servo system requires faster and more accurate dynamic responses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, a Fuzzy controller with a series of membership functions, and various sampling periods and rules, was designed on the basis of Lyapunov stability theory and auto tuning methods of input scale factors. And also it was showed to have the excellent adaptive performances against internal-external disturbances and the usefulness of this controller from the results of simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.586-589
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• 2005

Recently, the applications of unmanned system are steadily increasing. Unmanned automatic system is suitable for routine mission such as reconnaissance, environment monitoring, resource conservation and investigation. Especially, for the ocean environmental probe mission, many ocean engineers had scoped with the routine and even risky works. The unmanned surface vessel designed for sea probes can replace the periodic and routine missions such as water sampling, temperature and salinity measuring, etc. In this paper, an unmanned surface vessel was designed for ocean environmental probe missions. A classical and an adaptive fuzzy control system were designed and tested for the unmanned surface vessel. The design methodologies and performance of the surface vessel and fuzzy control algorithm were illustrated and verified with this unmanned vessel system designed for sea probes.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1045-1050
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• 1988

The problem of applying the linear integral filter in analysis and parameter estimation of linear continuous systems is discussed. A discrete-time model, which is equivalent to that obtained using the bilinear z transformation, is derived and employed to predict system output. It is shown that the output error can be controlled through the sampling interval. In order to obtain unbiased estimates, an instrumental variable (IV) method is proposed, where the instrumental variables are constituted using adaptive filtering. Some problems on implementation of the recursive IV algorithm are discussed. Both theoretical analysis and simulation study are given to illustrate the proposed methods.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.29-39
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• 2009

This article investigates economic-statistical design of VSSI(variable sampling size and interval) cause-selecting charts considering two assignable causes. We consider a process which is composed of two dependent sub-processes. In each sub-process, two kinds of assignable cause may exist. We propose a procedure for designing VSSI cause-selecting charts, based on Lorenzen and Vance model. Computational experiments show that the VSSI cause-selecting chart is superior to the FSSI cause-selecting chart in the economic-statistical characteristics, even under two assignable causes.