• 한국해양학회지
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• 제19권2호
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• pp.133-140
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• 1984

디지탈필터(digital filter) 중에서 특히 순환필터(recursive filter)와 Hamming window를 사용한 종합필터(convolution filter)의 해양학적 응용에 대해 논하였다. 종합필터는 이해하기 쉬우며 설계가 간단하지만, 자료수가 많은 경우에는 비경제 적이다. 순환필터는 설계가 다소 복잡하지만, 필터의 특성이 좋으며 경제적이다. 여름철(1973∼1979) 부산 해안선에 평행한 바람과 감포의 표면해수온도간에 저주파(주기 5일 이상) 성분은 상관관계가 뚜렷하나, 고주파 성분은 상관관계가 거의 없음을 디지탈필터를 사용함으로써 밝혀 내었다.

• 대한전자공학회논문지SP
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• 제46권4호
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• pp.132-138
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• 2009

본 논문에서는 기존의 Minima Controlled Recursive Averaging (MCRA)에 2차 조건 사후 최대 확률기법을 적용한 음성 향상 기법을 제안한다. 기존의 MCRA 방법은 현제 프레임의 음성 신호 존재 확률로 잡음 추정을 조정하기 때문에 음성 활동의 프레임간의 상호 연관성을 배제 하였다. 본 논문에서 제안한 알고리즘은 직전 2 프레임에서의 음성의 존재와 부재에 대한 조건을 부여해 주어 현제 프레임의 음성 신호 존재 확률을 수정하는 음성향상 기법을 적용한다. 제안된 2차 조건 사후 최대 확률기법을 적용한 MCRA 방법이 기존의 MCRA 방법보다 향상된 음성향상 결과를 나타내었다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집E
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• pp.536-541
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• 2001

A high resolution digital cinematic Particle Image Velocimetry(PIV) has been developed. The system consists of a high speed CCD camera, a continuous Ar-ion laser and a computer with camera controller. To improve the spatial resolution, we adopt a Recursive Technique for velocity interrogation. At first, we obtain a velocity vector for a larger interrogation window size based on the conventional two-frame cross-correlation PIV analysis using the FFT algorithm. Based on the knowing velocity information, more spatially resolved velocity vectors are obtained in the next iteration step with smaller interrogation windows. The correct velocity vector at the first step is found to be critical, so we apply a Multiple Correlation Validation(MCV) technique in order to decrease the spurious vectors. The MCV technique turns out to improve SNR(Signal to Noise Ratio) of the correlation table. The developed cinematic PIV method has been applied to the measurement of the unsteady flow characteristics of a Rushton turbine mixer. A total of 3,245 instantaneous velocity vectors were successfully obtained with 4 ms time resolution. The acquired spatial resolution corresponds the performance of the conventional high resolution digital PIV system using a $1K{\times}1K$ CCD camera.

• 대한기계학회논문집B
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• 제25권11호
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• pp.1535-1542
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• 2001

A high resolution digital cinematic Particle Image Velocimetry(PIV) has been developed. The system consists of a high speed CCD camera, a continuous Ar-ion laser and a computer with camera controller. To improve the spatial resolution, we adopt a Recursive Technique for velocity interrogation. At first, we obtain a velocity vector fur a larger interrogation window size based on the conventional two-frame cross-correlation PIV analysis using the FFT algorithm. Based on the knowing velocity information, more spatially resolved velocity vectors are obtained in the next iteration step with smaller interrogation windows. When the correct velocity vector at the first step is found to be critical, a Multiple Correlation Validation(MCV) technique is applied to decrease the spurious vectors. The MCV technique turns out to improve SNR(Signal to Noise Ratio) of the correlation table. The developed cinematic PIV method has been applied to the measurement of the unsteady flow characteristics of a Rushton turbine mixer. A total of 3,245 instantaneous velocity vectors were successfully obtained with 4 ms time resolution. The acquired spatial resolution corresponds to the conventional high resolution digital PIV system using a 1K ${\times}$ 1K CCD camera.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.305-307
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• 1992

This paper presents a technique, which identifies both process noise covariance and sensor noise covariance by using innovation correlation test. A correlation test, which checks whether the square root Kalman filter is workingly optimal or not, is given. The system is stochastic autoregressive moving-average model with auxiliary white noise Input. The linear quadratic Gaussian control is used for minimizing stochastic cost function. This paper indentifies Q, R, and estimates parametric matrics $A(q^{-1}),B(q^{-1}),C(q^{-1})$ by means of extended recursive least squares and model reference control. And The proposed technique has been validated in simulation results on the fourth order system.

• 소음진동
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• 제8권1호
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• pp.203-211
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• 1998

In order to find out relationship between hit probability and gun firing of a moving tank, a turret and flexible gun system model has been developed using a recursive flexible multibody dynamics. For a firing simulation model, nodal coordinates for a finite element model of a flexible gun have been employed to include transverse loads to the gun tube due to moving bullet and ballistic pressure. Modal coordinates are also used to represent the motion induced gun vibration before a firing occurs. An efficient switching technique from modal equations to nodal equation has been introduced for an entire gun firing simulation with a rotating turret.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.242-245
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• 2009

This paper proposes an algorithm that increases the speed of generating a Fresnel hologram using a recursive addition operation covering the whole coordinate array of a digital hologram. The 3D object designed to calculate the digital hologram used the depth-map image produced by computer graphics (CG). The proposed algorithm is a technique that performs CGH (computer generated hologram) operation with only the recursive addition from the hologram's whole coordinates by analyzing the regularity between the 3D object and the digital hologram coordinates. The experimental results showed that the proposed algorithm increased operation speed by 30% over the technique using the conventional CGH equation.

• Smart Structures and Systems
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• 제11권1호
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

• 전기학회논문지
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• 제64권1호
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• pp.99-106
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• 2015

In this study, we propose Radial basis function Neural Network(RBFNN) using Recursive Weighted Least Square Estimation(RWLSE) to effectively deal with big data class meteorological radar data. In the condition part of the RBFNN, Fuzzy C-Means(FCM) clustering is used to obtain fitness values taking into account characteristics of input data, and connection weights are defined as linear polynomial function in the conclusion part. The coefficients of the polynomial function are estimated by using RWLSE in order to cope with big data. As recursive learning technique, RWLSE which is based on WLSE is carried out to efficiently process big data. This study is experimented with both widely used some Machine Learning (ML) dataset and big data obtained from meteorological radar to evaluate the performance of the proposed classifier. The meteorological radar data as big data consists of precipitation echo and non-precipitation echo, and the proposed classifier is used to efficiently classify these echoes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.